Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2308.10486	Deep Metric Loss for Multimodal Learning	Multimodal learning often outperforms its unimodal counterparts by exploiting unimodal contributions and cross-modal interactions. However, focusing only on integrating multimodal features into a unified comprehensive representation overlooks the unimodal characteristics. In real data, the contributions of modalities c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	386,751
2401.13248	"Here's Your Evidence": False Consensus in Public Twitter Discussions of COVID-19 Science	The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific c...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	423,668
2109.00995	COVID-19 epidemic control using short-term lockdowns for collective gain	While many efforts are currently devoted to vaccines development and administration, social distancing measures, including severe restrictions such as lockdowns, remain fundamental tools to contain the spread of COVID-19. A crucial point for any government is to understand, on the basis of the epidemic curve, the right...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	253,311
2112.11790	BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View	Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving the 2D object detection task inspires us to seek an elegant, feasible, and scalable paradigm for fundamentally pushing the performance boundar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	272,803
1705.08480	Efficiently applying attention to sequential data with the Recurrent Discounted Attention unit	Recurrent Neural Networks architectures excel at processing sequences by modelling dependencies over different timescales. The recently introduced Recurrent Weighted Average (RWA) unit captures long term dependencies far better than an LSTM on several challenging tasks. The RWA achieves this by applying attention to ea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,026
2006.11375	Segmentation task for fashion and apparel	The Fashion Industry is a strong and important industry in the global economy. Globalization has brought fast fashion, quick shifting consumer shopping preferences, more competition, and abundance in fashion shops and retailers, making it more difficult for professionals in the fashion industry to keep track of what fa...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	183,194
2105.11748	Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients	Automatic lesion segmentation on thoracic CT enables rapid quantitative analysis of lung involvement in COVID-19 infections. However, obtaining a large amount of voxel-level annotations for training segmentation networks is prohibitively expensive. Therefore, we propose a weakly-supervised segmentation method based on ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	236,812
1710.09334	A unified framework for manifold landmarking	The success of semi-supervised manifold learning is highly dependent on the quality of the labeled samples. Active manifold learning aims to select and label representative landmarks on a manifold from a given set of samples to improve semi-supervised manifold learning. In this paper, we propose a novel active manifold...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,193
2311.12133	High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation	Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the existing scientific error-bounded lossy compressors, some of them (such as SPERR and FAZ) can reach fairly high compression ratios and some ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	409,215
2211.11603	Model-based Trajectory Stitching for Improved Offline Reinforcement Learning	In many real-world applications, collecting large and high-quality datasets may be too costly or impractical. Offline reinforcement learning (RL) aims to infer an optimal decision-making policy from a fixed set of data. Getting the most information from historical data is then vital for good performance once the policy...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,801
1808.04437	Discriminative multi-view Privileged Information learning for image re-ranking	Conventional multi-view re-ranking methods usually perform asymmetrical matching between the region of interest (ROI) in the query image and the whole target image for similarity computation. Due to the inconsistency in the visual appearance, this practice tends to degrade the retrieval accuracy particularly when the i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	105,140
1604.05508	Intelligent Agent-Based Stimulation for Testing Robotic Software in Human-Robot Interactions	The challenges of robotic software testing extend beyond conventional software testing. Valid, realistic and interesting tests need to be generated for multiple programs and hardware running concurrently, deployed into dynamic environments with people. We investigate the use of Belief-Desire-Intention (BDI) agents as m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	54,822
1401.3863	An Effective Algorithm for and Phase Transitions of the Directed Hamiltonian Cycle Problem	The Hamiltonian cycle problem (HCP) is an important combinatorial problem with applications in many areas. It is among the first problems used for studying intrinsic properties, including phase transitions, of combinatorial problems. While thorough theoretical and experimental analyses have been made on the HCP in undi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	29,977
1808.00309	Model-order selection in statistical shape models	Statistical shape models enhance machine learning algorithms providing prior information about deformation. A Point Distribution Model (PDM) is a popular landmark-based statistical shape model for segmentation. It requires choosing a model order, which determines how much of the variation seen in the training data is a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	104,362
1804.10765	Specifying and Verbalising Answer Set Programs in Controlled Natural Language	We show how a bi-directional grammar can be used to specify and verbalise answer set programs in controlled natural language. We start from a program specification in controlled natural language and translate this specification automatically into an executable answer set program. The resulting answer set program can be...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	96,223
2104.05115	Disentangling Semantics and Syntax in Sentence Embeddings with Pre-trained Language Models	Pre-trained language models have achieved huge success on a wide range of NLP tasks. However, contextual representations from pre-trained models contain entangled semantic and syntactic information, and therefore cannot be directly used to derive useful semantic sentence embeddings for some tasks. Paraphrase pairs offe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,605
2408.08484	An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem	The Maximum Minimal Cut Problem (MMCP), a NP-hard combinatorial optimization (CO) problem, has not received much attention due to the demanding and challenging bi-connectivity constraint. Moreover, as a CO problem, it is also a daunting task for machine learning, especially without labeled instances. To deal with these...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	481,007
1909.06138	Relative Generalized Hamming weights of affine Cartesian codes	We explicitly determine all the relative generalized Hamming weights of affine Cartesian codes using the notion of footprints and results from extremal combinatorics. This generalizes the previous works on the determination of relative generalized Hamming weights of Reed-Muller codes by Geil and Martin, as well as the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	145,300
1501.00287	Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics	We study consistency of learning algorithms for a multi-class performance metric that is a non-decomposable function of the confusion matrix of a classifier and cannot be expressed as a sum of losses on individual data points; examples of such performance metrics include the macro F-measure popular in information retri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	38,974
2104.13228	To mock a Mocking bird : Studies in Biomimicry	This paper dwells on certain novel game-theoretic investigations in bio-mimicry, discussed from the perspectives of information asymmetry, individual utility and its optimization via strategic interactions involving co-evolving preys (e.g., insects) and predators (e.g., reptiles) who learn. Formally, we consider a panm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	232,444
1812.01828	Graph based Question Answering System	In today's digital age in the dawning era of big data analytics it is not the information but the linking of information through entities and actions which defines the discourse. Any textual data either available on the Internet off off-line (like newspaper data, Wikipedia dump, etc) is basically connect information wh...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	115,626
2204.08454	Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images	Remote-sensing (RS) Change Detection (CD) aims to detect "changes of interest" from co-registered bi-temporal images. The performance of existing deep supervised CD methods is attributed to the large amounts of annotated data used to train the networks. However, annotating large amounts of remote sensing images is labo...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	292,084
2211.09253	Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications	Recent interest in integrated sensing and communications has led to the design of novel signal processing techniques to recover information from an overlaid radar-communications signal. Here, we focus on a spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	330,916
2407.06354	High-Throughput Phenotyping using Computer Vision and Machine Learning	High-throughput phenotyping refers to the non-destructive and efficient evaluation of plant phenotypes. In recent years, it has been coupled with machine learning in order to improve the process of phenotyping plants by increasing efficiency in handling large datasets and developing methods for the extraction of specif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,372
1610.03474	The Core of the Participatory Budgeting Problem	In participatory budgeting, communities collectively decide on the allocation of public tax dollars for local public projects. In this work, we consider the question of fairly aggregating the preferences of community members to determine an allocation of funds to projects. This problem is different from standard fair r...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	true	62,249
2310.06500	MetaAgents: Simulating Interactions of Human Behaviors for LLM-based Task-oriented Coordination via Collaborative Generative Agents	Significant advancements have occurred in the application of Large Language Models (LLMs) for various tasks and social simulations. Despite this, their capacities to coordinate within task-oriented social contexts are under-explored. Such capabilities are crucial if LLMs are to effectively mimic human-like social behav...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	398,605
2302.11848	Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit	Name disambiguation -- a fundamental problem in online academic systems -- is now facing greater challenges with the increasing growth of research papers. For example, on AMiner, an online academic search platform, about 10% of names own more than 100 authors. Such real-world challenging cases have not been effectively...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	347,337
2006.03669	An Overview of Neural Network Compression	Overparameterized networks trained to convergence have shown impressive performance in domains such as computer vision and natural language processing. Pushing state of the art on salient tasks within these domains corresponds to these models becoming larger and more difficult for machine learning practitioners to use ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,389
2302.00776	Safe Interval Path Planning With Kinodynamic Constraints	Safe Interval Path Planning (SIPP) is a powerful algorithm for solving single-agent pathfinding problem when the agent is confined to a graph and certain vertices/edges of this graph are blocked at certain time intervals due to dynamic obstacles that populate the environment. Original SIPP algorithm relies on the assum...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	343,335
2204.04634	Intersection Prediction from Single 360{\deg} Image via Deep Detection of Possible Direction of Travel	Movie-Map, an interactive first-person-view map that engages the user in a simulated walking experience, comprises short 360{\deg} video segments separated by traffic intersections that are seamlessly connected according to the viewer's direction of travel. However, in wide urban-scale areas with numerous intersecting ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	290,724
2409.02363	Optimal Neural Network Approximation for High-Dimensional Continuous Functions	Recently, the authors of Shen Yang Zhang (JMLR, 2022) developed a neural network with width $36d(2d + 1)$ and depth $11$, which utilizes a special activation function called the elementary universal activation function, to achieve the super approximation property for functions in $C([a,b]^d)$. That is, the constructed ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,667
2204.06905	Making Markets for Information Security: The Role of Online Platforms in Bug Bounty Programs	Security is an essential cornerstone of functioning digital marketplaces and communities. If users doubt that data shared online will remain secure, they will withdraw from platforms. Even when firms take these risks seriously, security expertise is expensive and vulnerabilities are diverse in nature. Increasingly, fir...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	291,487
2012.14469	On the computation of the slow dynamics of nonlinear modes of mechanical systems	A novel method for the numerical prediction of the slowly varying dynamics of nonlinear mechanical systems has been developed. The method is restricted to the regime of an isolated nonlinear mode and consists of a two-step procedure: In the first step, a multiharmonic analysis of the autonomous system is performed to d...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	213,518
2103.00782	Sparse Activity Detection in Multi-Cell Massive MIMO Exploiting Channel Large-Scale Fading	This paper studies the device activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system, in which the active devices transmit signature sequences to multiple base stations (BSs) that are connected to a central unit (CU), and the BSs cooperate across multiple cells to detect the act...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	222,397
2106.12042	HydroPower Plant Planning for Resilience Improvement of Power Systems using Fuzzy-Neural based Genetic Algorithm	This paper will propose a novel technique for optimize hydropower plant in small scale based on load frequency control (LFC) which use self-tuning fuzzy Proportional- Derivative (PD) method for estimation and prediction of planning. Due to frequency is not controlled by any dump load or something else, so this power pl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	242,595
1911.13152	Induction of Subgoal Automata for Reinforcement Learning	In this work we present ISA, a novel approach for learning and exploiting subgoals in reinforcement learning (RL). Our method relies on inducing an automaton whose transitions are subgoals expressed as propositional formulas over a set of observable events. A state-of-the-art inductive logic programming system is used ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	155,593
2207.13475	PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on	Image-based virtual try-on is one of the most promising applications of human-centric image generation due to its tremendous real-world potential. In this work, we take a step forwards to explore versatile virtual try-on solutions, which we argue should possess three main properties, namely, they should support unsuper...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,321
1710.06537	Sim-to-Real Transfer of Robotic Control with Dynamics Randomization	Simulations are attractive environments for training agents as they provide an abundant source of data and alleviate certain safety concerns during the training process. But the behaviours developed by agents in simulation are often specific to the characteristics of the simulator. Due to modeling error, strategies tha...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	82,792
2107.00729	Essence of Factual Knowledge	Knowledge bases are collections of domain-specific and commonsense facts. Recently, the sizes of KBs are rocketing due to automatic extraction for knowledge and facts. For example, the number of facts in WikiData is up to 974 million! According to our observation, current KBs, especially domain KBs, show strong relevan...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	244,252
2502.13968	Betsu-Betsu: Multi-View Separable 3D Reconstruction of Two Interacting Objects	Separable 3D reconstruction of multiple objects from multi-view RGB images -- resulting in two different 3D shapes for the two objects with a clear separation between them -- remains a sparsely researched problem. It is challenging due to severe mutual occlusions and ambiguities along the objects' interaction boundarie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	535,600
2306.06800	AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing	Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we present AraMUS, the largest Arabic PLM with 11B parameters trained on 529GB of high-quality Arabic textual data. AraMUS achieves state-of-the-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	372,755
1707.00577	Generalization Properties of Doubly Stochastic Learning Algorithms	Doubly stochastic learning algorithms are scalable kernel methods that perform very well in practice. However, their generalization properties are not well understood and their analysis is challenging since the corresponding learning sequence may not be in the hypothesis space induced by the kernel. In this paper, we p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	76,376
2103.15483	Adaptive Surface Normal Constraint for Depth Estimation	We present a novel method for single image depth estimation using surface normal constraints. Existing depth estimation methods either suffer from the lack of geometric constraints, or are limited to the difficulty of reliably capturing geometric context, which leads to a bottleneck of depth estimation quality. We ther...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,225
1908.11515	Improving Utility and Security of the Shuffler-based Differential Privacy	When collecting information, local differential privacy (LDP) alleviates privacy concerns of users because their private information is randomized before being sent it to the central aggregator. LDP imposes large amount of noise as each user executes the randomization independently. To address this issue, recent work i...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	true	143,400
1503.02779	On metric properties of maps between Hamming spaces and related graph homomorphisms	A mapping of $k$-bit strings into $n$-bit strings is called an $(\alpha,\beta)$-map if $k$-bit strings which are more than $\alpha k$ apart are mapped to $n$-bit strings that are more than $\beta n$ apart. This is a relaxation of the classical problem of constructing error-correcting codes, which corresponds to $\alpha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,969
2203.05961	Random Ensemble Reinforcement Learning for Traffic Signal Control	Traffic signal control is a significant part of the construction of intelligent transportation. An efficient traffic signal control strategy can reduce traffic congestion, improve urban road traffic efficiency and facilitate people's lives. Existing reinforcement learning approaches for traffic signal control mainly fo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	284,971
1605.06167	Combining Density and Overlap (CoDO): A New Method for Assessing the Significance of Overlap Among Subgraphs	Algorithms for detecting clusters (including overlapping clusters) in graphs have received significant attention in the research community. A closely related important aspect of the problem -- quantification of statistical significance of overlap of clusters, remains relatively unexplored. This paper presents the first...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	56,091
2312.04067	MeanCut: A Greedy-Optimized Graph Clustering via Path-based Similarity and Degree Descent Criterion	As the most typical graph clustering method, spectral clustering is popular and attractive due to the remarkable performance, easy implementation, and strong adaptability. Classical spectral clustering measures the edge weights of graph using pairwise Euclidean-based metric, and solves the optimal graph partition by re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	413,538
2005.12469	CARPe Posterum: A Convolutional Approach for Real-time Pedestrian Path Prediction	Pedestrian path prediction is an essential topic in computer vision and video understanding. Having insight into the movement of pedestrians is crucial for ensuring safe operation in a variety of applications including autonomous vehicles, social robots, and environmental monitoring. Current works in this area utilize ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,732
2304.06372	Contact Models in Robotics: a Comparative Analysis	Physics simulation is ubiquitous in robotics. Whether in model-based approaches (e.g., trajectory optimization), or model-free algorithms (e.g., reinforcement learning), physics simulators are a central component of modern control pipelines in robotics. Over the past decades, several robotic simulators have been develo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	357,954
2105.02345	A Multi-Chamber Smart Suction Cup for Adaptive Gripping and Haptic Exploration	We present a novel robot end-effector for gripping and haptic exploration. Tactile sensing through suction flow monitoring is applied to a new suction cup design that contains multiple chambers for air flow. Each chamber connects with its own remote pressure transducer, which enables both absolute and differential pres...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	233,789
2212.09400	Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension	Drug-drug interaction prediction is a crucial issue in molecular biology. Traditional methods of observing drug-drug interactions through medical experiments require significant resources and labor. This paper presents a medical knowledge graph question answering model, dubbed MedKGQA, that predicts drug-drug interacti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,099
1705.10720	Low Impact Artificial Intelligences	There are many goals for an AI that could become dangerous if the AI becomes superintelligent or otherwise powerful. Much work on the AI control problem has been focused on constructing AI goals that are safe even for such AIs. This paper looks at an alternative approach: defining a general concept of `low impact'. The...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	74,456
2402.12558	Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19	COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	430,894
2205.00204	Minimization of Secrecy Outage Probability in Reconfigurable Intelligent Surface-Assisted MIMOME System	This article investigates physical layer security (PLS) in reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) channels. Existing researches ignore the problem that secrecy rate can not be calculated if the eavesdropper's instantaneous channel state in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	294,166
1707.00670	Efficient Discovering of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data	We consider the problem of discovering sequential patterns from event-based spatio-temporal data. The dataset is described by a set of event types and their instances. Based on the given dataset, the task is to discover all significant sequential patterns denoting some attraction relation between event types occurring ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	76,392
cs/0602022	Avoiding the Bloat with Stochastic Grammar-based Genetic Programming	The application of Genetic Programming to the discovery of empirical laws is often impaired by the huge size of the search space, and consequently by the computer resources needed. In many cases, the extreme demand for memory and CPU is due to the massive growth of non-coding segments, the introns. The paper presents a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,257
2410.18074	UnCLe: Unsupervised Continual Learning of Depth Completion	We propose UnCLe, a standardized benchmark for Unsupervised Continual Learning of a multimodal depth estimation task: Depth completion aims to infer a dense depth map from a pair of synchronized RGB image and sparse depth map. We benchmark depth completion models under the practical scenario of unsupervised learning ov...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	501,725
2406.11928	FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction	Multimodal electronic health record (EHR) data can offer a holistic assessment of a patient's health status, supporting various predictive healthcare tasks. Recently, several studies have embraced the multitask learning approach in the healthcare domain, exploiting the inherent correlations among clinical tasks to pred...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	465,151
1904.08103	Multi-Scale Geometric Consistency Guided Multi-View Stereo	In this paper, we propose an efficient multi-scale geometric consistency guided multi-view stereo method for accurate and complete depth map estimation. We first present our basic multi-view stereo method with Adaptive Checkerboard sampling and Multi-Hypothesis joint view selection (ACMH). It leverages structured regio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,973
2108.02002	Online unsupervised Learning for domain shift in COVID-19 CT scan datasets	Neural networks often require large amounts of expert annotated data to train. When changes are made in the process of medical imaging, trained networks may not perform as well, and obtaining large amounts of expert annotations for each change in the imaging process can be time consuming and expensive. Online unsupervi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,189
2106.15361	Quantifying urban streetscapes with deep learning: focus on aesthetic evaluation	The disorder of urban streetscapes would negatively affect people's perception of their aesthetic quality. The presence of billboards on building facades has been regarded as an important factor of the disorder, but its quantification methodology has not yet been developed in a scalable manner. To fill the gap, this pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	243,741
1103.2325	Self reference in word definitions	Dictionaries are inherently circular in nature. A given word is linked to a set of alternative words (the definition) which in turn point to further descendants. Iterating through definitions in this way, one typically finds that definitions loop back upon themselves. The graph formed by such definitional relations is ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	9,572
2306.07685	Few-shot Multi-domain Knowledge Rearming for Context-aware Defence against Advanced Persistent Threats	Advanced persistent threats (APTs) have novel features such as multi-stage penetration, highly-tailored intention, and evasive tactics. APTs defense requires fusing multi-dimensional Cyber threat intelligence data to identify attack intentions and conducts efficient knowledge discovery strategies by data-driven machine...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	373,112
2207.08215	Optimizing out-of-plane stiffness for soft grippers	In this paper, we presented a data-driven framework to optimize the out-of-plane stiffness for soft grippers to achieve mechanical properties as hard-to-twist and easy-to-bend. The effectiveness of this method is demonstrated in the design of a soft pneumatic bending actuator (SPBA). First, a new objective function is ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	308,505
2410.02200	Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts	Prompt-based techniques, such as prompt-tuning and prefix-tuning, have gained prominence for their efficiency in fine-tuning large pre-trained models. Despite their widespread adoption, the theoretical foundations of these methods remain limited. For instance, in prefix-tuning, we observe that a key factor in achieving...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	494,163
2406.00984	Predicting Drug-Gene Relations via Analogy Tasks with Word Embeddings	Natural language processing (NLP) is utilized in a wide range of fields, where words in text are typically transformed into feature vectors called embeddings. BioConceptVec is a specific example of embeddings tailored for biology, trained on approximately 30 million PubMed abstracts using models such as skip-gram. Gene...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	460,113
2207.13757	The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteria	Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criteria are often most naturally described in free-text, using language familiar to clinicians and researchers. In order to identify potential pa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	310,390
2408.04846	UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs	Numerical solvers of Partial Differential Equations (PDEs) are of fundamental significance to science and engineering. To date, the historical reliance on legacy techniques has circumscribed possible integration of big data knowledge and exhibits sub-optimal efficiency for certain PDE formulations, while data-driven ne...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	479,555
2412.10524	Is Polarization an Inevitable Outcome of Similarity-Based Content Recommendations? -- Mathematical Proofs and Computational Validation	The increasing reliance on digital platforms shapes how individuals understand the world, as recommendation systems direct users toward content "similar" to their existing preferences. While this process simplifies information retrieval, there is concern that it may foster insular communities, so-called echo chambers, ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	516,978
1712.03632	Robust Deep Reinforcement Learning with Adversarial Attacks	This paper proposes adversarial attacks for Reinforcement Learning (RL) and then improves the robustness of Deep Reinforcement Learning algorithms (DRL) to parameter uncertainties with the help of these attacks. We show that even a naively engineered attack successfully degrades the performance of DRL algorithm. We fur...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	86,482
2008.08262	Quarantines as a Targeted Immunization Strategy	In the context of the recent COVID-19 outbreak, quarantine has been used to "flatten the curve" and slow the spread of the disease. In this paper, we show that this is not the only benefit of quarantine for the mitigation of an SIR epidemic spreading on a graph. Indeed, human contact networks exhibit a powerlaw structu...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	192,368
2307.10212	Capsule network with shortcut routing	This study introduces "shortcut routing," a novel routing mechanism in capsule networks that addresses computational inefficiencies by directly activating global capsules from local capsules, eliminating intermediate layers. An attention-based approach with fuzzy coefficients is also explored for improved efficiency. E...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,465
1512.01768	Want Answers? A Reddit Inspired Study on How to Pose Questions	Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information need and in extending our knowledge boundaries. A question may be represented using various factors such as social, syntactic, semantic, etc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	49,859
2005.13616	Modality Dropout for Improved Performance-driven Talking Faces	We describe our novel deep learning approach for driving animated faces using both acoustic and visual information. In particular, speech-related facial movements are generated using audiovisual information, and non-speech facial movements are generated using only visual information. To ensure that our model exploits b...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,053
1509.01208	Fast Clustering and Topic Modeling Based on Rank-2 Nonnegative Matrix Factorization	The importance of unsupervised clustering and topic modeling is well recognized with ever-increasing volumes of text data. In this paper, we propose a fast method for hierarchical clustering and topic modeling called HierNMF2. Our method is based on fast Rank-2 nonnegative matrix factorization (NMF) that performs binar...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	46,579
1508.06270	Extending UML-RT for Control System Modeling	There is a growing interest in adopting object technologies for the development of real-time control systems. Several commercial tools, currently available, provide object-oriented modeling and design support for real-time control systems. While these products provide many useful facilities, such as visualization tools...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	46,311
1905.10041	Efficient Batch Black-box Optimization with Deterministic Regret Bounds	In this work, we investigate black-box optimization from the perspective of frequentist kernel methods. We propose a novel batch optimization algorithm, which jointly maximizes the acquisition function and select points from a whole batch in a holistic way. Theoretically, we derive regret bounds for both the noise-free...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,931
2403.13553	VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model	Conversational artificial intelligence can already independently engage in brief conversations with clients with psychological problems and provide evidence-based psychological interventions. The main objective of this study is to improve the effectiveness and credibility of the large language model in psychological in...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	439,679
2402.09715	DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service	Federated learning (FL) has emerged as a prevalent distributed machine learning scheme that enables collaborative model training without aggregating raw data. Cloud service providers further embrace Federated Learning as a Service (FLaaS), allowing data analysts to execute their FL training pipelines over differentiall...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	429,644
1211.5888	User Scheduling for Coordinated Dual Satellite Systems with Linear Precoding	The constantly increasing demand for interactive broadband satellite communications is driving current research to explore novel system architectures that reuse frequency in a more aggressive manner. To this end, the topic of dual satellite systems, in which satellites share spatial (i.e. same coverage area) and spectr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,937
2212.01529	Laplacian Convolutional Representation for Traffic Time Series Imputation	Spatiotemporal traffic data imputation is of great significance in intelligent transportation systems and data-driven decision-making processes. To perform efficient learning and accurate reconstruction from partially observed traffic data, we assert the importance of characterizing both global and local trends in time...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	334,463
1810.04452	AI Learns to Recognize Bengali Handwritten Digits: Bengali.AI Computer Vision Challenge 2018	Solving problems with Artificial intelligence in a competitive manner has long been absent in Bangladesh and Bengali-speaking community. On the other hand, there has not been a well structured database for Bengali Handwritten digits for mass public use. To bring out the best minds working in machine learning and use th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	110,046
2206.04149	A Survey of Graph-based Deep Learning for Anomaly Detection in Distributed Systems	Anomaly detection is a crucial task in complex distributed systems. A thorough understanding of the requirements and challenges of anomaly detection is pivotal to the security of such systems, especially for real-world deployment. While there are many works and application domains that deal with this problem, few have ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,519
2201.01466	Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence	Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has ac...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	274,262
2412.15579	Score-based Generative Diffusion Models for Social Recommendations	With the prevalence of social networks on online platforms, social recommendation has become a vital technique for enhancing personalized recommendations. The effectiveness of social recommendations largely relies on the social homophily assumption, which presumes that individuals with social connections often share si...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	519,186
2411.18314	Real-time Video Target Tracking Algorithm Utilizing Convolutional Neural Networks (CNN)	Thispaperaimstoresearchandimplementa real-timevideotargettrackingalgorithmbasedon ConvolutionalNeuralNetworks(CNN),enhancingthe accuracyandrobustnessoftargettrackingincomplex scenarios.Addressingthelimitationsoftraditionaltracking algorithmsinhandlingissuessuchastargetocclusion,morphologicalchanges,andbackgroundinterfe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,827
2312.12116	Length 3 Check Digit Codes with Grouped Tags and Disjoint Coding Applications	In 1969 J. Verhoeff provided the first examples of a decimal error detecting code using a single check digit to provide protection against all single, transposition, and adjacent twin errors. The three codes he presented are length 3-digit codes with 2 information digits. To date, the existence of a length 4-digit code...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	416,847
1509.00126	Dynamic Network Formation with Foresighted Agents	What networks can form and persist when agents are self-interested? Can such networks be efficient? A substantial theoretical literature predicts that the only networks that can form and persist must have very special shapes and that such networks cannot be efficient, but these predictions are in stark contrast to empi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	46,467
0808.0596	On row-by-row coding for 2-D constraints	A constant-rate encoder--decoder pair is presented for a fairly large family of two-dimensional (2-D) constraints. Encoding and decoding is done in a row-by-row manner, and is sliding-block decodable. Essentially, the 2-D constraint is turned into a set of independent and relatively simple one-dimensional (1-D) const...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,165
2311.00719	Is Human Culture Locked by Evolution?	Human culture has evolved for thousands of years and thrived in the era of Internet. Due to the availability of big data, we could do research on human culture by analyzing its representation such as user item rating values on websites like MovieLens and Douban. Industrial workers have applied recommender systems in bi...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	404,748
2411.11939	Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging	Deep learning has achieved remarkable success in image classification and segmentation tasks. However, fairness concerns persist, as models often exhibit biases that disproportionately affect demographic groups defined by sensitive attributes such as race, gender, or age. Existing bias-mitigation techniques, including ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,246
2411.03742	Adaptive Consensus Gradients Aggregation for Scaled Distributed Training	Distributed machine learning has recently become a critical paradigm for training large models on vast datasets. We examine the stochastic optimization problem for deep learning within synchronous parallel computing environments under communication constraints. While averaging distributed gradients is the most widely u...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	506,020
2403.05700	DADIT: A Dataset for Demographic Classification of Italian Twitter Users and a Comparison of Prediction Methods	Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the general public. To facilitate such analyses, we construct, validate, and release publicly the representative DADIT dataset of 30M tweets of 20k Italian Twitter users, along with their bio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	436,110
2303.04658	Global Localization in Unstructured Environments using Semantic Object Maps Built from Various Viewpoints	We present a novel framework for global localization and guided relocalization of a vehicle in an unstructured environment. Compared to existing methods, our pipeline does not rely on cues from urban fixtures (e.g., lane markings, buildings), nor does it make assumptions that require the vehicle to be navigating on a r...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	350,170
2409.17544	Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings	Theoretical and empirical evidence suggests that joint graph embedding algorithms induce correlation across the networks in the embedding space. In the Omnibus joint graph embedding framework, previous results explicitly delineated the dual effects of the algorithm-induced and model-inherent correlations on the correla...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	491,857
2502.11881	Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models	Existing LLM reasoning methods have shown impressive capabilities across various tasks, such as solving math and coding problems. However, applying these methods to scenarios without ground-truth answers or rule-based verification methods - such as tracking the mental states of an agent - remains challenging. Inspired ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,583
2407.02945	VEGS: View Extrapolation of Urban Scenes in 3D Gaussian Splatting using Learned Priors	Neural rendering-based urban scene reconstruction methods commonly rely on images collected from driving vehicles with cameras facing and moving forward. Although these methods can successfully synthesize from views similar to training camera trajectory, directing the novel view outside the training camera distribution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,957
2305.09288	A Dictionary-based approach to Time Series Ordinal Classification	Time Series Classification (TSC) is an extensively researched field from which a broad range of real-world problems can be addressed obtaining excellent results. One sort of the approaches performing well are the so-called dictionary-based techniques. The Temporal Dictionary Ensemble (TDE) is the current state-of-the-a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	364,588
2006.15366	ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification	Despite achieving state-of-the-art performance, deep learning methods generally require a large amount of labeled data during training and may suffer from overfitting when the sample size is small. To ensure good generalizability of deep networks under small sample sizes, learning discriminative features is crucial. To...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	184,482

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.