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
1208.0055	Large-scale continuous subgraph queries on streams	Graph pattern matching involves finding exact or approximate matches for a query subgraph in a larger graph. It has been studied extensively and has strong applications in domains such as computer vision, computational biology, social networks, security and finance. The problem of exact graph pattern matching is often ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	17,847
1505.06685	On the Multivariate Gamma-Gamma ($\Gamma \Gamma$) Distribution with Arbitrary Correlation and Applications in Wireless Communications	The statistical properties of the multivariate Gamma-Gamma ($\Gamma \Gamma$) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (PDF), cumulative distribution function (CDF) and moment generation function of the mult...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,462
2211.11137	Long Range Constraints for Neural Texture Synthesis Using Sliced Wasserstein Loss	In the past decade, exemplar-based texture synthesis algorithms have seen strong gains in performance by matching statistics of deep convolutional neural networks. However, these algorithms require regularization terms or user-added spatial tags to capture long range constraints in images. Having access to a user-added...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,595
2408.02214	More Than Positive and Negative: Communicating Fine Granularity in Medical Diagnosis	With the advance of deep learning, much progress has been made in building powerful artificial intelligence (AI) systems for automatic Chest X-ray (CXR) analysis. Most existing AI models are trained to be a binary classifier with the aim of distinguishing positive and negative cases. However, a large gap exists between...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,545
2302.06470	POSGen: Personalized Opening Sentence Generation for Online Insurance Sales	The insurance industry is shifting their sales mode from offline to online, in expectation to reach massive potential customers in the digitization era. Due to the complexity and the nature of insurance products, a cost-effective online sales solution is to exploit chatbot AI to raise customers' attention and pass thos...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	345,418
2410.12536	SiFiSinger: A High-Fidelity End-to-End Singing Voice Synthesizer based on Source-filter Model	This paper presents an advanced end-to-end singing voice synthesis (SVS) system based on the source-filter mechanism that directly translates lyrical and melodic cues into expressive and high-fidelity human-like singing. Similarly to VISinger 2, the proposed system also utilizes training paradigms evolved from VITS and...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	499,076
2405.11526	Register assisted aggregation for Visual Place Recognition	Visual Place Recognition (VPR) refers to the process of using computer vision to recognize the position of the current query image. Due to the significant changes in appearance caused by season, lighting, and time spans between query images and database images for retrieval, these differences increase the difficulty of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	455,180
2310.01565	Causality-informed Rapid Post-hurricane Building Damage Detection in Large Scale from InSAR Imagery	Timely and accurate assessment of hurricane-induced building damage is crucial for effective post-hurricane response and recovery efforts. Recently, remote sensing technologies provide large-scale optical or Interferometric Synthetic Aperture Radar (InSAR) imagery data immediately after a disastrous event, which can be...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	396,471
1103.5410	Political protest Italian-style: The dissonance between the blogosphere and mainstream media in the promotion and coverage of Beppe Grillo's V-day	We analyze the organization, promotion and public perception of V-day, a political rally that took place on September 8, 2007, to protest against corruption in the Italian Parliament. Launched by blogger Beppe Grillo, and promoted via a word of mouth mobilization on the Italian blogosphere, V-day brought close to one m...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	9,784
1811.01837	TzK Flow - Conditional Generative Model	We introduce TzK (pronounced "task"), a conditional probability flow-based model that exploits attributes (e.g., style, class membership, or other side information) in order to learn tight conditional prior around manifolds of the target observations. The model is trained via approximated ML, and offers efficient appro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,456
2309.04459	Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning	Exploration in sparse-reward reinforcement learning is difficult due to the requirement of long, coordinated sequences of actions in order to achieve any reward. Moreover, in continuous action spaces there are an infinite number of possible actions, which only increases the difficulty of exploration. One class of metho...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	390,733
2310.06838	AutoAD II: The Sequel -- Who, When, and What in Movie Audio Description	Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences. For movies, this presents notable challenges -- AD must occur only during existing pauses in dialogue, should refer to characters by name, and ought to aid underst...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,732
1701.01325	Outlier Detection for Text Data : An Extended Version	The problem of outlier detection is extremely challenging in many domains such as text, in which the attribute values are typically non-negative, and most values are zero. In such cases, it often becomes difficult to separate the outliers from the natural variations in the patterns in the underlying data. In this paper...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	66,390
2304.08538	Robust Control Barrier Functions with Uncertainty Estimation	This paper proposes a safety controller for control-affine nonlinear systems with unmodelled dynamics and disturbances to improve closed-loop robustness. Uncertainty estimation-based control barrier functions (CBFs) are utilized to ensure robust safety in the presence of model uncertainties, which may depend on control...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	358,747
2307.07604	Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes	Fingerprinting arguments, first introduced by Bun, Ullman, and Vadhan (STOC 2014), are the most widely used method for establishing lower bounds on the sample complexity or error of approximately differentially private (DP) algorithms. Still, there are many problems in differential privacy for which we don't know suita...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	379,469
2209.15206	What Makes Pre-trained Language Models Better Zero-shot Learners?	Current methods for prompt learning in zeroshot scenarios widely rely on a development set with sufficient human-annotated data to select the best-performing prompt template a posteriori. This is not ideal because in a realworld zero-shot scenario of practical relevance, no labelled data is available. Thus, we propose ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	320,513
1402.0429	Defmod - Parallel multiphysics finite element code for modeling crustal deformation during the earthquake/rifting cycle	In this article, we present Defmod, an open source, fully unstructured, two or three dimensional, parallel finite element code for modeling crustal deformation over time scales ranging from milliseconds to thousands of years. Unlike existing public domain numerical codes, Defmod can simulate deformation due to all majo...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	30,563
2408.16040	Fairness, Accuracy, and Unreliable Data	This thesis investigates three areas targeted at improving the reliability of machine learning; fairness in machine learning, strategic classification, and algorithmic robustness. Each of these domains has special properties or structure that can complicate learning. A theme throughout this thesis is thinking about way...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	484,177
2403.05025	Debiased Multimodal Understanding for Human Language Sequences	Human multimodal language understanding (MLU) is an indispensable component of expression analysis (e.g., sentiment or humor) from heterogeneous modalities, including visual postures, linguistic contents, and acoustic behaviours. Existing works invariably focus on designing sophisticated structures or fusion strategies...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	435,833
2304.00761	Learning Anchor Transformations for 3D Garment Animation	This paper proposes an anchor-based deformation model, namely AnchorDEF, to predict 3D garment animation from a body motion sequence. It deforms a garment mesh template by a mixture of rigid transformations with extra nonlinear displacements. A set of anchors around the mesh surface is introduced to guide the learning ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,804
2007.08614	Dynamic Low-light Imaging with Quanta Image Sensors	Imaging in low light is difficult because the number of photons arriving at the sensor is low. Imaging dynamic scenes in low-light environments is even more difficult because as the scene moves, pixels in adjacent frames need to be aligned before they can be denoised. Conventional CMOS image sensors (CIS) are at a part...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,680
2102.04671	A Single-Timescale Method for Stochastic Bilevel Optimization	Stochastic bilevel optimization generalizes the classic stochastic optimization from the minimization of a single objective to the minimization of an objective function that depends the solution of another optimization problem. Recently, stochastic bilevel optimization is regaining popularity in emerging machine learni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,186
1508.02933	No Regret Bound for Extreme Bandits	Algorithms for hyperparameter optimization abound, all of which work well under different and often unverifiable assumptions. Motivated by the general challenge of sequentially choosing which algorithm to use, we study the more specific task of choosing among distributions to use for random hyperparameter optimization....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	45,954
1207.4120	Stable Independance and Complexity of Representation	The representation of independence relations generally builds upon the well-known semigraphoid axioms of independence. Recently, a representation has been proposed that captures a set of dominant statements of an independence relation from which any other statement can be generated by means of the axioms; the cardinali...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	17,547
2410.15270	Can LVLMs Describe Videos like Humans? A Five-in-One Video Annotations Benchmark for Better Human-Machine Comparison	Large vision-language models (LVLMs) have made significant strides in addressing complex video tasks, sparking researchers' interest in their human-like multimodal understanding capabilities. Video description serves as a fundamental task for evaluating video comprehension, necessitating a deep understanding of spatial...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	500,451
1901.09181	Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware	Artificial Neural Networks (ANNs) have emerged as hot topics in the research community. Despite the success of ANNs, it is challenging to train and deploy modern ANNs on commodity hardware due to the ever-increasing model size and the unprecedented growth in the data volumes. Particularly for microarray data, the very-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	119,669
2106.08367	What Context Features Can Transformer Language Models Use?	Transformer-based language models benefit from conditioning on contexts of hundreds to thousands of previous tokens. What aspects of these contexts contribute to accurate model prediction? We describe a series of experiments that measure usable information by selectively ablating lexical and structural information in t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	241,264
2012.04510	Graph-based open-ended survey on concerns related to COVID-19	The COVID-19 pandemic is an unprecedented public health crisis with broad social and economic consequences. We conducted four surveys between April and August 2020 using the graph-based open-ended survey (GOS) framework, and investigated the most pressing concerns and issues for the general public in Japan. The GOS fra...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	210,475
1603.06390	Learning Dynamic Robot-to-Human Object Handover from Human Feedback	Object handover is a basic, but essential capability for robots interacting with humans in many applications, e.g., caring for the elderly and assisting workers in manufacturing workshops. It appears deceptively simple, as humans perform object handover almost flawlessly. The success of humans, however, belies the comp...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	53,488
2212.09668	Task-Oriented Communications for NextG: End-to-End Deep Learning and AI Security Aspects	Communications systems to date are primarily designed with the goal of reliable transfer of digital sequences (bits). Next generation (NextG) communication systems are beginning to explore shifting this design paradigm to reliably executing a given task such as in task-oriented communications. In this paper, wireless s...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	true	337,185
1507.06120	Towards Storytelling from Visual Lifelogging: An Overview	Visual lifelogging consists of acquiring images that capture the daily experiences of the user by wearing a camera over a long period of time. The pictures taken offer considerable potential for knowledge mining concerning how people live their lives, hence, they open up new opportunities for many potential application...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,363
1903.06498	Stripe: Tensor Compilation via the Nested Polyhedral Model	Hardware architectures and machine learning (ML) libraries evolve rapidly. Traditional compilers often fail to generate high-performance code across the spectrum of new hardware offerings. To mitigate, engineers develop hand-tuned kernels for each ML library update and hardware upgrade. Unfortunately, this approach req...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	124,398
2212.04175	GreenEyes: An Air Quality Evaluating Model based on WaveNet	Accompanying rapid industrialization, humans are suffering from serious air pollution problems. The demand for air quality prediction is becoming more and more important to the government's policy-making and people's daily life. In this paper, We propose GreenEyes -- a deep neural network model, which consists of a Wav...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	335,352
1909.02490	Neuromorphic Visual Odometry System for Intelligent Vehicle Application with Bio-inspired Vision Sensor	The neuromorphic camera is a brand new vision sensor that has emerged in recent years. In contrast to the conventional frame-based camera, the neuromorphic camera only transmits local pixel-level changes at the time of its occurrence and provides an asynchronous event stream with low latency. It has the advantages of e...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	144,212
2110.00272	Learn to Communicate with Neural Calibration: Scalability and Generalization	The conventional design of wireless communication systems typically relies on established mathematical models that capture the characteristics of different communication modules. Unfortunately, such design cannot be easily and directly applied to future wireless networks, which will be characterized by large-scale ultr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,341
2003.13883	Autonomous Cave Surveying with an Aerial Robot	This paper presents a method for cave surveying in total darkness using an autonomous aerial vehicle equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights. Traditional methods of cave surveying are labor-intensive and dangerous due to the risk of hypother...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	170,340
2409.16382	Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints	Recognizing pain in video is crucial for improving patient-computer interaction systems, yet traditional data collection in this domain raises significant ethical and logistical challenges. This study introduces a novel approach that leverages synthetic data to enhance video-based pain recognition models, providing an ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,316
2308.11455	A Survey on Self-Supervised Representation Learning	Learning meaningful representations is at the heart of many tasks in the field of modern machine learning. Recently, a lot of methods were introduced that allow learning of image representations without supervision. These representations can then be used in downstream tasks like classification or object detection. The ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,145
2405.09042	Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering	Intent modeling has attracted widespread attention in recommender systems. As the core motivation behind user selection of items, intent is crucial for elucidating recommendation results. The current mainstream modeling method is to abstract the intent into unknowable but learnable shared or non-shared parameters. Desp...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	454,281
2111.03212	An overview of event extraction and its applications	With the rapid development of information technology, online platforms have produced enormous text resources. As a particular form of Information Extraction (IE), Event Extraction (EE) has gained increasing popularity due to its ability to automatically extract events from human language. However, there are limited lit...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	265,090
1812.07179	Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving	3D object detection is an essential task in autonomous driving. Recent techniques excel with highly accurate detection rates, provided the 3D input data is obtained from precise but expensive LiDAR technology. Approaches based on cheaper monocular or stereo imagery data have, until now, resulted in drastically lower ac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,772
2004.07777	Gaze-Net: Appearance-Based Gaze Estimation using Capsule Networks	Recent studies on appearance based gaze estimation indicate the ability of Neural Networks to decode gaze information from facial images encompassing pose information. In this paper, we propose Gaze-Net: A capsule network capable of decoding, representing, and estimating gaze information from ocular region images. We e...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	172,872
1302.4721	Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station	We study resource allocation algorithm design for energy-efficient communication in an OFDMA downlink network with hybrid energy harvesting base station. Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,175
2408.00113	Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models	What latent features are encoded in language model (LM) representations? Recent work on training sparse autoencoders (SAEs) to disentangle interpretable features in LM representations has shown significant promise. However, evaluating the quality of these SAEs is difficult because we lack a ground-truth collection of i...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	477,708
1912.00664	Training the Convolutional Neural Network with Statistical Dependence of the Response on the Input Data Distortion	The paper proposes an approach to training a convolutional neural network using information on the level of distortion of input data. The learning process is modified with an additional layer, which is subsequently deleted, so the architecture of the original network does not change. As an example, the LeNet5 architect...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,851
1907.10420	A Deep Neural Network for Short-Segment Speaker Recognition	Todays interactive devices such as smart-phone assistants and smart speakers often deal with short-duration speech segments. As a result, speaker recognition systems integrated into such devices will be much better suited with models capable of performing the recognition task with short-duration utterances. In this pap...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,619
2412.06135	A CT Image Denoising Method Based on Projection Domain Feature	In order to improve image quality of projection in industrial applications, generally, a standard method is to increase the current or exposure time, which might cause overexposure of detector units in areas of thin objects or backgrounds. Increasing the projection sampling is a better method to address the issue, but ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,103
1810.12558	Relative Importance Sampling For Off-Policy Actor-Critic in Deep Reinforcement Learning	Off-policy learning is more unstable compared to on-policy learning in reinforcement learning (RL). One reason for the instability of off-policy learning is a discrepancy between the target ($\pi$) and behavior (b) policy distributions. The discrepancy between $\pi$ and b distributions can be alleviated by employing a ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	111,799
1807.08483	A Statistical Update of Grid Representations from Range Sensors	In a wide range of robotic applications, being able to create a 3D model of the surrounding environment is a key feature for autonomous tasks. In this research report, we present a statistical model to perform 3D reconstructions of the environment from range sensors using an occupancy grid. To do so, we take into accou...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	103,552
2411.03702	Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving	The growing demand for robust scene understanding in mobile robotics and autonomous driving has highlighted the importance of integrating multiple sensing modalities. By combining data from diverse sensors like cameras and LIDARs, fusion techniques can overcome the limitations of individual sensors, enabling a more com...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	506,001
2109.05391	Gradients and Subgradients of Buffered Failure Probability	Gradients and subgradients are central to optimization and sensitivity analysis of buffered failure probabilities. We furnish a characterization of subgradients based on subdifferential calculus in the case of finite probability distributions and, under additional assumptions, also a gradient expression for general dis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	254,773
1501.00642	Unsupervised Feature Learning for Dense Correspondences across Scenes	We propose a fast, accurate matching method for estimating dense pixel correspondences across scenes. It is a challenging problem to estimate dense pixel correspondences between images depicting different scenes or instances of the same object category. While most such matching methods rely on hand-crafted features suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,009
2006.14163	Geometric Prediction: Moving Beyond Scalars	Many quantities we are interested in predicting are geometric tensors; we refer to this class of problems as geometric prediction. Attempts to perform geometric prediction in real-world scenarios have been limited to approximating them through scalar predictions, leading to losses in data efficiency. In this work, we d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,138
2307.05646	Better Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models	Customer feedback is invaluable to companies as they refine their products. Monitoring customer feedback can be automated with Aspect Level Sentiment Classification (ALSC) which allows us to analyse specific aspects of the products in reviews. Large Language Models (LLMs) are the heart of many state-of-the-art ALSC sol...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	378,819
2310.00936	Trained Latent Space Navigation to Prevent Lack of Photorealism in Generated Images on Style-based Models	Recent studies on StyleGAN variants show promising performances for various generation tasks. In these models, latent codes have traditionally been manipulated and searched for the desired images. However, this approach sometimes suffers from a lack of photorealism in generated images due to a lack of knowledge about t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	396,216
2301.13380	Automated Time-frequency Domain Audio Crossfades using Graph Cuts	The problem of transitioning smoothly from one audio clip to another arises in many music consumption scenarios, especially as music consumption has moved from professionally curated and live-streamed radios to personal playback devices and services. we present the first steps toward a new method of automatically trans...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,887
2111.15031	MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels	Malware family classification is a significant issue with public safety and research implications that has been hindered by the high cost of expert labels. The vast majority of corpora use noisy labeling approaches that obstruct definitive quantification of results and study of deeper interactions. In order to provide ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	268,781
2312.00088	Anomaly Detection via Learning-Based Sequential Controlled Sensing	In this paper, we address the problem of detecting anomalies among a given set of binary processes via learning-based controlled sensing. Each process is parameterized by a binary random variable indicating whether the process is anomalous. To identify the anomalies, the decision-making agent is allowed to observe a su...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	411,904
2210.02978	Remembering Netizens: An interview with Ronda Hauben, co-author of Netizens: On the history and impact of Usenet and the Internet (1997)	Netizens, Michael and Ronda Hauben's foundational treatise on Usenet and the Internet, was first published in print 25 years ago. In this piece, we trace the history and impact of the book and of Usenet itself, contextualising them within the contemporary and modern-day scholarship on virtual communities, online cultur...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	321,847
2404.04015	A Flexible Evolutionary Algorithm With Dynamic Mutation Rate Archive	We propose a new, flexible approach for dynamically maintaining successful mutation rates in evolutionary algorithms using $k$-bit flip mutations. The algorithm adds successful mutation rates to an archive of promising rates that are favored in subsequent steps. Rates expire when their number of unsuccessful trials has...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	444,484
1708.02287	Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inference	Monocular depth estimation is a challenging task in complex compositions depicting multiple objects of diverse scales. Albeit the recent great progress thanks to the deep convolutional neural networks (CNNs), the state-of-the-art monocular depth estimation methods still fall short to handle such real-world challenging ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,561
2106.04804	EMFlow: Data Imputation in Latent Space via EM and Deep Flow Models	The presence of missing values within high-dimensional data is an ubiquitous problem for many applied sciences. A serious limitation of many available data mining and machine learning methods is their inability to handle partially missing values and so an integrated approach that combines imputation and model estimatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,861
2401.17783	SDRDPy: An application to graphically visualize the knowledge obtained with supervised descriptive rule algorithms	SDRDPy is a desktop application that allows experts an intuitive graphic and tabular representation of the knowledge extracted by any supervised descriptive rule discovery algorithm. The application is able to provide an analysis of the data showing the relevant information of the data set and the relationship between ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	425,320
1312.5946	Adaptive Seeding for Gaussian Mixture Models	We present new initialization methods for the expectation-maximization algorithm for multivariate Gaussian mixture models. Our methods are adaptions of the well-known $K$-means++ initialization and the Gonzalez algorithm. Thereby we aim to close the gap between simple random, e.g. uniform, and complex methods, that cru...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	29,286
1105.1922	Numerical Construction of LISS Lyapunov Functions under a Small Gain Condition	In the stability analysis of large-scale interconnected systems it is frequently desirable to be able to determine a decay point of the gain operator, i.e., a point whose image under the monotone operator is strictly smaller than the point itself. The set of such decay points plays a crucial role in checking, in a semi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	10,311
1806.04841	A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition	Speech recognizers trained on close-talking speech do not generalize to distant speech and the word error rate degradation can be as large as 40% absolute. Most studies focus on tackling distant speech recognition as a separate problem, leaving little effort to adapting close-talking speech recognizers to distant speec...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	100,332
2308.11358	How Much Temporal Long-Term Context is Needed for Action Segmentation?	Modeling long-term context in videos is crucial for many fine-grained tasks including temporal action segmentation. An interesting question that is still open is how much long-term temporal context is needed for optimal performance. While transformers can model the long-term context of a video, this becomes computation...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	387,109
2305.05672	$2 * n$ is better than $n^2$: Decomposing Event Coreference Resolution into Two Tractable Problems	Event Coreference Resolution (ECR) is the task of linking mentions of the same event either within or across documents. Most mention pairs are not coreferent, yet many that are coreferent can be identified through simple techniques such as lemma matching of the event triggers or the sentences in which they appear. Exis...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	363,245
2401.09266	P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering	Deep clustering, which learns representation and semantic clustering without labels information, poses a great challenge for deep learning-based approaches. Despite significant progress in recent years, most existing methods focus on uniformly distributed datasets, significantly limiting the practical applicability of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,206
2304.13413	Secure Communication Model For Quantum Federated Learning: A Post Quantum Cryptography (PQC) Framework	We design a model of Post Quantum Cryptography (PQC) Quantum Federated Learning (QFL). We develop a framework with a dynamic server selection and study convergence and security conditions. The implementation and results are publicly available1.	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	360,567
2106.08413	Robust Reinforcement Learning Under Minimax Regret for Green Security	Green security domains feature defenders who plan patrols in the face of uncertainty about the adversarial behavior of poachers, illegal loggers, and illegal fishers. Importantly, the deterrence effect of patrols on adversaries' future behavior makes patrol planning a sequential decision-making problem. Therefore, we f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	241,278
2012.14661	Parzen Window Approximation on Riemannian Manifold	In graph motivated learning, label propagation largely depends on data affinity represented as edges between connected data points. The affinity assignment implicitly assumes even distribution of data on the manifold. This assumption may not hold and may lead to inaccurate metric assignment due to drift towards high-de...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	213,575
2409.16809	Analytical assessment of workers' safety concerning direct and indirect ways of getting infected by dangerous pathogen	Developing safety policies to protect large groups of individuals working in indoor environments from disease spread is an important and challenging task. To address this issue, we investigate the scenario of workers becoming infected by a dangerous airborne pathogen in a near-real-life industrial environment. We prese...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	491,520
2404.11208	CAGE: Causality-Aware Shapley Value for Global Explanations	As Artificial Intelligence (AI) is having more influence on our everyday lives, it becomes important that AI-based decisions are transparent and explainable. As a consequence, the field of eXplainable AI (or XAI) has become popular in recent years. One way to explain AI models is to elucidate the predictive importance ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	447,422
1809.02345	Hierarchical Characteristic Set Merging for Optimizing SPARQL Queries in Heterogeneous RDF	Characteristic sets (CS) organize RDF triples based on the set of properties characterizing their subject nodes. This concept is recently used in indexing techniques, as it can capture the implicit schema of RDF data. While most CS-based approaches yield significant improvements in space and query performance, they fai...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	107,034
1902.07007	Improving dual-arm assembly by master-slave compliance	In this paper we show how different choices regarding compliance affect a dual-arm assembly task. In addition, we present how the compliance parameters can be learned from a human demonstration. Compliant motions can be used in assembly tasks to mitigate pose errors originating from, for example, inaccurate grasping. W...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	121,895
2401.01361	Optimizing Convolutional Neural Network Architecture	Convolutional Neural Networks (CNN) are widely used to face challenging tasks like speech recognition, natural language processing or computer vision. As CNN architectures get larger and more complex, their computational requirements increase, incurring significant energetic costs and challenging their deployment on re...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	419,323
1912.02861	Exposing Fake Images with Forensic Similarity Graphs	We propose new image forgery detection and localization algorithms by recasting these problems as graph-based community detection problems. To do this, we introduce a novel abstract, graph-based representation of an image, which we call the Forensic Similarity Graph, that captures key forensic relationships among regio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,448
2305.12409	Deep Radar Inverse Sensor Models for Dynamic Occupancy Grid Maps	To implement autonomous driving, one essential step is to model the vehicle environment based on the sensor inputs. Radars, with their well-known advantages, became a popular option to infer the occupancy state of grid cells surrounding the vehicle. To tackle data sparsity and noise of radar detections, we propose a de...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	365,985
2305.15233	Cross-lingual QA: A Key to Unlocking In-context Cross-lingual Performance	Multilingual large language models (MLLMs) have demonstrated significant cross-lingual capabilities through in-context learning. Existing approaches typically construct monolingual in-context examples, either in the source or target language. However, translating entire in-context examples into the target language migh...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	367,517
2202.11860	Robust Transmission Design for RIS-assisted Secure Multiuser Communication Systems in the Presence of Hardware Impairments	This paper investigates reconfigurable intelligent surface (RIS)-assisted secure multiuser communication systems subject to hardware impairments (HIs). We jointly optimize the beamforming vectors at the base station (BS) and the phase shifts of the reflecting elements at the RIS so as to maximize the weighted minimum s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	282,024
2104.04121	Fast, Smart Neuromorphic Sensors Based on Heterogeneous Networks and Mixed Encodings	Neuromorphic architectures are ideally suited for the implementation of smart sensors able to react, learn, and respond to a changing environment. Our work uses the insect brain as a model to understand how heterogeneous architectures, incorporating different types of neurons and encodings, can be leveraged to create s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	229,296
2207.07706	Probing Semantic Grounding in Language Models of Code with Representational Similarity Analysis	Representational Similarity Analysis is a method from cognitive neuroscience, which helps in comparing representations from two different sources of data. In this paper, we propose using Representational Similarity Analysis to probe the semantic grounding in language models of code. We probe representations from the Co...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	308,278
2310.15484	NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA	Multi-hop Knowledge Graph Question Answering (KGQA) is a task that involves retrieving nodes from a knowledge graph (KG) to answer natural language questions. Recent GNN-based approaches formulate this task as a KG path searching problem, where messages are sequentially propagated from the seed node towards the answer ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	402,329
2204.11167	RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning	Reasoning about visual relationships is central to how humans interpret the visual world. This task remains challenging for current deep learning algorithms since it requires addressing three key technical problems jointly: 1) identifying object entities and their properties, 2) inferring semantic relations between pai...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	293,057
2407.20535	DeepSpeech models show Human-like Performance and Processing of Cochlear Implant Inputs	Cochlear implants(CIs) are arguably the most successful neural implant, having restored hearing to over one million people worldwide. While CI research has focused on modeling the cochlear activations in response to low-level acoustic features, we hypothesize that the success of these implants is due in large part to t...	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	477,195
2105.14891	ACNet: Mask-Aware Attention with Dynamic Context Enhancement for Robust Acne Detection	Computer-aided diagnosis has recently received attention for its advantage of low cost and time efficiency. Although deep learning played a major role in the recent success of acne detection, there are still several challenges such as color shift by inconsistent illumination, variation in scales, and high density distr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,844
2408.08900	Towards Effective Authorship Attribution: Integrating Class-Incremental Learning	AA is the process of attributing an unidentified document to its true author from a predefined group of known candidates, each possessing multiple samples. The nature of AA necessitates accommodating emerging new authors, as each individual must be considered unique. This uniqueness can be attributed to various factors...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	481,197
1805.07027	Efficient Downlink Channel Reconstruction for FDD Multi-Antenna Systems	In this paper, we propose an efficient downlink channel reconstruction scheme for a frequency-division-duplex multi-antenna system by utilizing uplink channel state information combined with limited feedback. Based on the spatial reciprocity in a wireless channel, the downlink channel is reconstructed by using frequenc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	97,722
2210.01225	Force-Aware Interface via Electromyography for Natural VR/AR Interaction	While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual world remains challenging. Closing the gap between real-world physicality and immersive virtual experience requires a closed interaction loop: ...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	321,167
1707.00166	Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach	Relation extraction is a fundamental task in information extraction. Most existing methods have heavy reliance on annotations labeled by human experts, which are costly and time-consuming. To overcome this drawback, we propose a novel framework, REHession, to conduct relation extractor learning using annotations from h...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	76,304
1910.10702	Deep learning enabled laser speckle wavemeter with a high dynamic range	The speckle pattern produced when a laser is scattered by a disordered medium has recently been shown to give a surprisingly accurate or broadband measurement of wavelength. Here it is shown that deep learning is an ideal approach to analyse wavelength variations using a speckle wavemeter due to its ability to identify...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,563
2201.12910	Sparse Centroid-Encoder: A Nonlinear Model for Feature Selection	Autoencoders have been widely used as a nonlinear tool for data dimensionality reduction. While autoencoders don't utilize the label information, Centroid-Encoders (CE)\cite{ghosh2022supervised} use the class label in their learning process. In this study, we propose a sparse optimization using the Centroid-Encoder arc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	277,831
1805.02275	Coherence Modeling of Asynchronous Conversations: A Neural Entity Grid Approach	We propose a novel coherence model for written asynchronous conversations (e.g., forums, emails), and show its applications in coherence assessment and thread reconstruction tasks. We conduct our research in two steps. First, we propose improvements to the recently proposed neural entity grid model by lexicalizing its ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	96,823
2306.07087	MaskedFusion360: Reconstruct LiDAR Data by Querying Camera Features	In self-driving applications, LiDAR data provides accurate information about distances in 3D but lacks the semantic richness of camera data. Therefore, state-of-the-art methods for perception in urban scenes fuse data from both sensor types. In this work, we introduce a novel self-supervised method to fuse LiDAR and ca...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	372,875
cmp-lg/9510005	Developing and Evaluating a Probabilistic LR Parser of Part-of-Speech and Punctuation Labels	We describe an approach to robust domain-independent syntactic parsing of unrestricted naturally-occurring (English) input. The technique involves parsing sequences of part-of-speech and punctuation labels using a unification-based grammar coupled with a probabilistic LR parser. We describe the coverage of several corp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,466
2104.10592	Robust Biped Locomotion Using Deep Reinforcement Learning on Top of an Analytical Control Approach	This paper proposes a modular framework to generate robust biped locomotion using a tight coupling between an analytical walking approach and deep reinforcement learning. This framework is composed of six main modules which are hierarchically connected to reduce the overall complexity and increase its flexibility. The ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	231,634
2402.04059	Deep Learning for Multivariate Time Series Imputation: A Survey	Missing values are ubiquitous in multivariate time series (MTS) data, posing significant challenges for accurate analysis and downstream applications. In recent years, deep learning-based methods have successfully handled missing data by leveraging complex temporal dependencies and learned data distributions. In this s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	427,314
2102.00850	On Scaling Contrastive Representations for Low-Resource Speech Recognition	Recent advances in self-supervised learning through contrastive training have shown that it is possible to learn a competitive speech recognition system with as little as 10 minutes of labeled data. However, these systems are computationally expensive since they require pre-training followed by fine-tuning in a large p...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,936
1702.00505	Algorithmic Performance-Accuracy Trade-off in 3D Vision Applications Using HyperMapper	In this paper we investigate an emerging application, 3D scene understanding, likely to be significant in the mobile space in the near future. The goal of this exploration is to reduce execution time while meeting our quality of result objectives. In previous work we showed for the first time that it is possible to map...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	67,664

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