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
2305.03981	Pre-training Language Model as a Multi-perspective Course Learner	ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing performance, ELECTRA still faces the challenges of monotonous training and deficient interaction. Generator with only masked language modeling (MLM...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,590
2501.15042	SCCD: A Session-based Dataset for Chinese Cyberbullying Detection	The rampant spread of cyberbullying content poses a growing threat to societal well-being. However, research on cyberbullying detection in Chinese remains underdeveloped, primarily due to the lack of comprehensive and reliable datasets. Notably, no existing Chinese dataset is specifically tailored for cyberbullying det...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	527,370
2105.08601	Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection	The problem of decentralized multi-robot target tracking asks for jointly selecting actions, e.g., motion primitives, for the robots to maximize target tracking performance with local communications. One major challenge for practical implementations is to make target tracking approaches scalable for large-scale problem...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	true	false	false	false	235,809
2307.05449	On the hull and complementarity of one generator quasi-cyclic codes and four-circulant codes	We study one generator quasi-cyclic codes and four-circulant codes, which are also quasi-cyclic but have two generators. We state the hull dimensions for both classes of codes in terms of the polynomials in their generating elements. We prove results such as the hull dimension of a four-circulant code is even and one-d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	378,745
2002.12699	Automatic Section Recognition in Obituaries	Obituaries contain information about people's values across times and cultures, which makes them a useful resource for exploring cultural history. They are typically structured similarly, with sections corresponding to Personal Information, Biographical Sketch, Characteristics, Family, Gratitude, Tribute, Funeral Infor...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	166,116
1706.05394	A Closer Look at Memorization in Deep Networks	We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noise data, our results suggest that they tend to prioritize learning simple patterns first. In our experiments, we expose qualitative differen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,505
2006.15935	Is Japanese gendered language used on Twitter ? A large scale study	This study analyzes the usage of Japanese gendered language on Twitter. Starting from a collection of 408 million Japanese tweets from 2015 till 2019 and an additional sample of 2355 manually classified Twitter accounts timelines into gender and categories (politicians, musicians, etc). A large scale textual analysis i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	184,664
2309.12854	ThinResNet: A New Baseline for Structured Convolutional Networks Pruning	Pruning is a compression method which aims to improve the efficiency of neural networks by reducing their number of parameters while maintaining a good performance, thus enhancing the performance-to-cost ratio in nontrivial ways. Of particular interest are structured pruning techniques, in which whole portions of param...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	393,956
1606.02809	On Uplink User Capacity for Massive MIMO Cellular Networks	Under the conditions where performance in a massive MIMO network is limited by pilot contamination, the reverse link signal-to-interference ratio (SIR) exhibits different distributions when using different pilot allocation schemes. By utilising different sets of orthogonal pilot sequences, as opposed to reused sequence...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,017
1802.03644	Learning to Match via Inverse Optimal Transport	We propose a unified data-driven framework based on inverse optimal transport that can learn adaptive, nonlinear interaction cost function from noisy and incomplete empirical matching matrix and predict new matching in various matching contexts. We emphasize that the discrete optimal transport plays the role of a varia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,029
1804.04093	SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation	Supervised training of abstractive language generation models results in learning conditional probabilities over language sequences based on the supervised training signal. When the training signal contains a variety of writing styles, such models may end up learning an 'average' style that is directly influenced by th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	94,757
2202.11757	Degradation-Reducing Control for Dynamically Reconfigurable Batteries	Cascaded circuits such as modular multilevel con-verters (MMC) offer attractive qualities in reconfigurable battery applications. In contrast to conventional hard-wired dc battery packs, the MMC topology loads modules with ac current, which may lead to additional ageing of batteries. As recent studies reveal, such agei...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	281,983
1604.01651	Representing model inadequacy: A stochastic operator approach	Mathematical models of physical systems are subject to many uncertainties such as measurement errors and uncertain initial and boundary conditions. After accounting for these uncertainties, it is often revealed that discrepancies between the model output and the observations remain; if so, the model is said to be inade...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	54,220
1104.5391	On Optimality of Greedy Policy for a Class of Standard Reward Function of Restless Multi-armed Bandit Problem	In this paper,we consider the restless bandit problem, which is one of the most well-studied generalizations of the celebrated stochastic multi-armed bandit problem in decision theory. However, it is known be PSPACE-Hard to approximate to any non-trivial factor. Thus the optimality is very difficult to obtain due to it...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	10,156
1810.05561	Optimal Source Codes for Timely Updates	A transmitter observing a sequence of independent and identically distributed random variables seeks to keep a receiver updated about its latest observations. The receiver need not be apprised about each symbol seen by the transmitter, but needs to output a symbol at each time instant $t$. If at time $t$ the receiver o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	110,259
1609.02226	Fitted Learning: Models with Awareness of their Limits	Though deep learning has pushed the boundaries of classification forward, in recent years hints of the limits of standard classification have begun to emerge. Problems such as fooling, adding new classes over time, and the need to retrain learning models only for small changes to the original problem all point to a pot...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	60,704
2009.09488	Consistency, Acyclicity, and Positive Semirings	In several different settings, one comes across situations in which the objects of study are locally consistent but globally inconsistent. Earlier work about probability distributions by Vorob'ev (1962) and about database relations by Beeri, Fagin, Maier, Yannakakis (1983) produced characterizations of when local consi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	196,598
2406.00980	Selectively Answering Visual Questions	Recently, large multi-modal models (LMMs) have emerged with the capacity to perform vision tasks such as captioning and visual question answering (VQA) with unprecedented accuracy. Applications such as helping the blind or visually impaired have a critical need for precise answers. It is specially important for models ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	460,110
2303.17568	CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X	Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer. In this paper, we introduce CodeGeeX, a multilingual model with 13 billion parameters for code gener...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	355,252
2305.17575	Mobile Safety Application for Pedestrians	Vulnerable Road User (VRU) safety has been an important issue throughout the years as corresponding fatality numbers in traffic have been increasing each year. With the developments in connected vehicle technology, there are new and easier ways of implementing Vehicle to Everything (V2X) communication which can be util...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	368,659
1711.09485	SkipNet: Learning Dynamic Routing in Convolutional Networks	While deeper convolutional networks are needed to achieve maximum accuracy in visual perception tasks, for many inputs shallower networks are sufficient. We exploit this observation by learning to skip convolutional layers on a per-input basis. We introduce SkipNet, a modified residual network, that uses a gating netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,413
2409.16984	AXCEL: Automated eXplainable Consistency Evaluation using LLMs	Large Language Models (LLMs) are widely used in both industry and academia for various tasks, yet evaluating the consistency of generated text responses continues to be a challenge. Traditional metrics like ROUGE and BLEU show a weak correlation with human judgment. More sophisticated metrics using Natural Language Inf...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	491,605
2306.09147	Probabilistic Learning of Multivariate Time Series with Temporal Irregularity	Probabilistic forecasting of multivariate time series is essential for various downstream tasks. Most existing approaches rely on the sequences being uniformly spaced and aligned across all variables. However, real-world multivariate time series often suffer from temporal irregularities, including nonuniform intervals ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	373,696
1503.02302	DESAT: an SSW tool for SDO/AIA image de-saturation	Saturation affects a significant rate of images recorded by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory. This paper describes a computational method and a technological pipeline for the de-saturation of such images, based on several mathematical ingredients like Expectation Maximization, image co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	40,920
2302.14390	Your time series is worth a binary image: machine vision assisted deep framework for time series forecasting	Time series forecasting (TSF) has been a challenging research area, and various models have been developed to address this task. However, almost all these models are trained with numerical time series data, which is not as effectively processed by the neural system as visual information. To address this challenge, this...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	348,276
2402.06733	NICE: To Optimize In-Context Examples or Not?	Recent work shows that in-context learning and optimization of in-context examples (ICE) can significantly improve the accuracy of large language models (LLMs) on a wide range of tasks, leading to an apparent consensus that ICE optimization is crucial for better performance. However, most of these studies assume a fixe...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	428,415
2305.14764	Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning	We estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional neural networks. We propose a method to obtain a spatial map of physical parameters by estimating the parameters from patterns within a sma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,241
2310.18899	Multi-task deep learning for large-scale building detail extraction from high-resolution satellite imagery	Understanding urban dynamics and promoting sustainable development requires comprehensive insights about buildings. While geospatial artificial intelligence has advanced the extraction of such details from Earth observational data, existing methods often suffer from computational inefficiencies and inconsistencies when...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	403,755
1902.10756	Insights into LSTM Fully Convolutional Networks for Time Series Classification	Long Short Term Memory Fully Convolutional Neural Networks (LSTM-FCN) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve state-of-the-art performance on the task of classifying time series signals on the old University of California-Riverside (UCR) time series repository. However, there has been no study on why L...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,762
2401.01288	Physics-informed Generalizable Wireless Channel Modeling with Segmentation and Deep Learning: Fundamentals, Methodologies, and Challenges	Channel modeling is fundamental in advancing wireless systems and has thus attracted considerable research focus. Recent trends have seen a growing reliance on data-driven techniques to facilitate the modeling process and yield accurate channel predictions. In this work, we first provide a concise overview of data-driv...	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	false	false	419,304
1907.07556	Optimal Secure Control with Linear Temporal Logic Constraints	Prior work on automatic control synthesis for cyber-physical systems under logical constraints has primarily focused on environmental disturbances or modeling uncertainties, however, the impact of deliberate and malicious attacks has been less studied. In this paper, we consider a discrete-time dynamical system with a ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	138,906
1612.05441	A Message Passing Algorithm for the Minimum Cost Multicut Problem	We propose a dual decomposition and linear program relaxation of the NP -hard minimum cost multicut problem. Unlike other polyhedral relaxations of the multicut polytope, it is amenable to efficient optimization by message passing. Like other polyhedral elaxations, it can be tightened efficiently by cutting planes. We ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	65,682
2402.09623	Conformalized Adaptive Forecasting of Heterogeneous Trajectories	This paper presents a new conformal method for generating simultaneous forecasting bands guaranteed to cover the entire path of a new random trajectory with sufficiently high probability. Prompted by the need for dependable uncertainty estimates in motion planning applications where the behavior of diverse objects may ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,603
2310.03043	A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback	Interactive search can provide a better experience by incorporating interaction feedback from the users. This can significantly improve search accuracy as it helps avoid irrelevant information and captures the users' search intents. Existing state-of-the-art (SOTA) systems use reinforcement learning (RL) models to inco...	true	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	397,113
2210.13005	Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment	The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analysis and clinical treatment. In practice, the next-event prediction models are trained with sequential data collected at one time and need to ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	326,007
2412.02482	What should a neuron aim for? Designing local objective functions based on information theory	In modern deep neural networks, the learning dynamics of the individual neurons is often obscure, as the networks are trained via global optimization. Conversely, biological systems build on self-organized, local learning, achieving robustness and efficiency with limited global information. We here show how self-organi...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	513,553
2301.06796	Database Matching Under Noisy Synchronization Errors	The re-identification or de-anonymization of users from anonymized data through matching with publicly available correlated user data has raised privacy concerns, leading to the complementary measure of obfuscation in addition to anonymization. Recent research provides a fundamental understanding of the conditions unde...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	340,743
1904.03301	Hot Streaks on Social Media	Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's content as captured by metrics such as the number of views, likes, retweets, or s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	126,673
2009.13370	Replica Analysis of the Linear Model with Markov or Hidden Markov Signal Priors	This paper estimates free energy, average mutual information, and minimum mean square error (MMSE) of a linear model under two assumptions: (1) the source is generated by a Markov chain, (2) the source is generated via a hidden Markov model. Our estimates are based on the replica method in statistical physics. We show ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	197,728
2006.15090	Relative gradient optimization of the Jacobian term in unsupervised deep learning	Learning expressive probabilistic models correctly describing the data is a ubiquitous problem in machine learning. A popular approach for solving it is mapping the observations into a representation space with a simple joint distribution, which can typically be written as a product of its marginals -- thus drawing a c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,411
1909.03750	Combining SMT and NMT Back-Translated Data for Efficient NMT	Neural Machine Translation (NMT) models achieve their best performance when large sets of parallel data are used for training. Consequently, techniques for augmenting the training set have become popular recently. One of these methods is back-translation (Sennrich et al., 2016), which consists on generating synthetic s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	144,591
2407.15622	HyperSurf: Quadruped Robot Leg Capable of Surface Recognition with GRU and Real-to-Sim Transferring	This paper introduces a system of data collection acceleration and real-to-sim transferring for surface recognition on a quadruped robot. The system features a mechanical single-leg setup capable of stepping on various easily interchangeable surfaces. Additionally, it incorporates a GRU-based Surface Recognition System...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	475,261
2403.18874	Neural Attributed Community Search at Billion Scale	Community search has been extensively studied in the past decades. In recent years, there is a growing interest in attributed community search that aims to identify a community based on both the query nodes and query attributes. A set of techniques have been investigated. Though the recent methods based on advanced lea...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	442,117
2112.02057	Snake Robot Gait Decomposition and Gait Parameter Optimization	This paper proposes Gait Decomposition (G.D), a method of mathematically decomposing snake movements, and Gait Parameter Gradient (GPG), a method of optimizing decomposed gait parameters. G.D is a method that can express the snake gait mathematically and concisely from generating movement using the curve function to th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	269,714
2305.17926	Large Language Models are not Fair Evaluators	In this paper, we uncover a systematic bias in the evaluation paradigm of adopting large language models~(LLMs), e.g., GPT-4, as a referee to score and compare the quality of responses generated by candidate models. We find that the quality ranking of candidate responses can be easily hacked by simply altering their or...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	368,798
2401.17191	Semantic Belief Behavior Graph: Enabling Autonomous Robot Inspection in Unknown Environments	This paper addresses the problem of autonomous robotic inspection in complex and unknown environments. This capability is crucial for efficient and precise inspections in various real-world scenarios, even when faced with perceptual uncertainty and lack of prior knowledge of the environment. Existing methods for real-w...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	425,136
2110.00615	Predicting erectile dysfunction after treatment for localized prostate cancer	While the 10-year survival rate for localized prostate cancer patients is very good (>98%), side effects of treatment may limit quality of life significantly. Erectile dysfunction (ED) is a common burden associated with increasing age as well as prostate cancer treatment. Although many studies have investigated the fac...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	258,454
2202.00210	INPUT Team Description Paper in 2022	INPUT is a team participating in the RoboCup Soccer Small League (SSL). It aims to show the world the technological capabilities of the Nagaoka region of Niigata Prefecture, which is where the team members are from. For this purpose, we are working on one of the projects from the Nagaoka Activation Zone of Energy (NAZE...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	278,068
1903.09366	Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder	One problem in the application of reinforcement learning to real-world problems is the curse of dimensionality on the action space. Macro actions, a sequence of primitive actions, have been studied to diminish the dimensionality of the action space with regard to the time axis. However, previous studies relied on human...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	125,047
2304.05055	A Comprehensive Survey on Deep Graph Representation Learning	Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining. Classic graph embedding methods follow the basic idea that...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	357,466
2202.00567	Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation	In this paper, we focus on a new method of data augmentation to solve the data imbalance problem within imbalanced ECG datasets to improve the robustness and accuracy of heart disease detection. By using Optimal Transport, we augment the ECG disease data from normal ECG beats to balance the data among different categor...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	278,188
2210.00764	Relational program synthesis with numerical reasoning	Program synthesis approaches struggle to learn programs with numerical values. An especially difficult problem is learning continuous values over multiple examples, such as intervals. To overcome this limitation, we introduce an inductive logic programming approach which combines relational learning with numerical reas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	320,999
2403.05829	Measuring Robustness in Cyber-Physical Systems under Sensor Attacks	This paper contributes a formal framework for quantitative analysis of bounded sensor attacks on cyber-physical systems, using the formalism of differential dynamic logic. Given a precondition and postcondition of a system, we formalize two quantitative safety notions, quantitative forward and backward safety, which re...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	436,180
cs/0206026	Interleaved semantic interpretation in environment-based parsing	This paper extends a polynomial-time parsing algorithm that resolves structural ambiguity in input to a speech-based user interface by calculating and comparing the denotations of rival constituents, given some model of the interfaced application environment (Schuler 2001). The algorithm is extended to incorporate a fu...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,612
2102.04022	Towards Hierarchical Task Decomposition using Deep Reinforcement Learning for Pick and Place Subtasks	Deep Reinforcement Learning (DRL) is emerging as a promising approach to generate adaptive behaviors for robotic platforms. However, a major drawback of using DRL is the data-hungry training regime that requires millions of trial and error attempts, which is impractical when running experiments on robotic systems. Lear...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	218,964
2111.03731	Frugal Machine Learning	Machine learning, already at the core of increasingly many systems and applications, is set to become even more ubiquitous with the rapid rise of wearable devices and the Internet of Things. In most machine learning applications, the main focus is on the quality of the results achieved (e.g., prediction accuracy), and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,259
1906.04660	Two-step Constructive Approaches for Dungeon Generation	This paper presents a two-step generative approach for creating dungeons in the rogue-like puzzle game MiniDungeons 2. Generation is split into two steps, initially producing the architectural layout of the level as its walls and floor tiles, and then furnishing it with game objects representing the player's start and ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	134,790
2501.07766	Large Language Models for Knowledge Graph Embedding Techniques, Methods, and Challenges: A Survey	Large Language Models (LLMs) have attracted a lot of attention in various fields due to their superior performance, aiming to train hundreds of millions or more parameters on large amounts of text data to understand and generate natural language. As the superior performance of LLMs becomes apparent, they are increasing...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	524,504
2106.02394	On the Strategyproofness of the Geometric Median	The geometric median, an instrumental component of the secure machine learning toolbox, is known to be effective when robustly aggregating models (or gradients), gathered from potentially malicious (or strategic) users. What is less known is the extent to which the geometric median incentivizes dishonest behaviors. Thi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	238,858
2208.04360	SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022	The variability of wind power supply can present substantial challenges to incorporating wind power into a grid system. Thus, Wind Power Forecasting (WPF) has been widely recognized as one of the most critical issues in wind power integration and operation. There has been an explosion of studies on wind power forecasti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,084
2404.06287	Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training	The key to multi-label image classification (MLC) is to improve model performance by leveraging label correlations. Unfortunately, it has been shown that overemphasizing co-occurrence relationships can cause the overfitting issue of the model, ultimately leading to performance degradation. In this paper, we provide a c...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	445,407
1406.5979	Reinforcement and Imitation Learning via Interactive No-Regret Learning	Recent work has demonstrated that problems-- particularly imitation learning and structured prediction-- where a learner's predictions influence the input-distribution it is tested on can be naturally addressed by an interactive approach and analyzed using no-regret online learning. These approaches to imitation learni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	34,080
1505.06699	Simulation Algorithms with Exponential Integration for Time-Domain Analysis of Large-Scale Power Delivery Networks	We design an algorithmic framework using matrix exponentials for time-domain simulation of power delivery network (PDN). Our framework can reuse factorized matrices to simulate the large-scale linear PDN system with variable stepsizes. In contrast, current conventional PDN simulation solvers have to use fixed step-size...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	43,463
1407.0511	Braided Convolutional Codes -- A Class of Spatially Coupled Turbo-Like Codes	In this paper, we investigate the impact of spatial coupling on the thresholds of turbo-like codes. Parallel concatenated and serially concatenated convolutional codes as well as braided convolutional codes (BCCs) are compared by means of an exact density evolution (DE) analysis for the binary erasure channel (BEC). We...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,340
cs/0002015	Genetic Algorithms for Extension Search in Default Logic	A default theory can be characterized by its sets of plausible conclusions, called its extensions. But, due to the theoretical complexity of Default Logic (Sigma_2p-complete), the problem of finding such an extension is very difficult if one wants to deal with non trivial knowledge bases. Based on the principle of natu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	537,014
1703.03912	Mitigating the Curse of Correlation in Security Games by Entropy Maximization	In Stackelberg security games, a defender seeks to randomly allocate limited security resources to protect critical targets from an attack. In this paper, we study a fundamental, yet underexplored, phenomenon in security games, which we term the \emph{Curse of Correlation} (CoC). Specifically, we observe that there are...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	true	69,795
2310.10851	Tracking China's cross-strait bot networks against Taiwan	The cross-strait relationship between China and Taiwan is marked by increasing hostility around potential reunification. We analyze an unattributed bot network and how repeater bots engaged in an influence campaign against Taiwan following US House Speaker Nancy Pelosi's visit to Taiwan in 2022. We examine the message ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	400,408
2407.14564	APS-USCT: Ultrasound Computed Tomography on Sparse Data via AI-Physic Synergy	Ultrasound computed tomography (USCT) is a promising technique that achieves superior medical imaging reconstruction resolution by fully leveraging waveform information, outperforming conventional ultrasound methods. Despite its advantages, high-quality USCT reconstruction relies on extensive data acquisition by a larg...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	474,829
2112.07746	CEM-GD: Cross-Entropy Method with Gradient Descent Planner for Model-Based Reinforcement Learning	Current state-of-the-art model-based reinforcement learning algorithms use trajectory sampling methods, such as the Cross-Entropy Method (CEM), for planning in continuous control settings. These zeroth-order optimizers require sampling a large number of trajectory rollouts to select an optimal action, which scales poor...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	271,570
2104.06328	List Message Passing Decoding of Non-binary Low-Density Parity-Check Codes	A decoding algorithm for $q$-ary low-density parity-check codes over the $q$-ary symmetric channel is introduced. The exchanged messages are lists of symbols from $\Fq$. A density evolution analysis for maximum list sizes $1$ and $2$ is developed. Thresholds for selected regular low-density parity-check code ensembles ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	230,036
1708.03431	Iterative Deep Convolutional Encoder-Decoder Network for Medical Image Segmentation	In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,775
2404.13821	Robotic Blended Sonification: Consequential Robot Sound as Creative Material for Human-Robot Interaction	Current research in robotic sounds generally focuses on either masking the consequential sound produced by the robot or on sonifying data about the robot to create a synthetic robot sound. We propose to capture, modify, and utilise rather than mask the sounds that robots are already producing. In short, this approach r...	true	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	448,456
1710.10932	Structure-preserving discrete-time optimal maneuvers of a wheeled inverted pendulum	The Wheeled Inverted Pendulum (WIP) is a nonholonomic, underactuated mechanical system, and has been popularized commercially as the {\it Segway}. Designing optimal control laws for point-to-point state-transfer for this autonomous mechanical system, while respecting momentum and torque constraints as well as the under...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	83,495
2310.19990	Unveiling the Limits of Learned Local Search Heuristics: Are You the Mightiest of the Meek?	In recent years, combining neural networks with local search heuristics has become popular in the field of combinatorial optimization. Despite its considerable computational demands, this approach has exhibited promising outcomes with minimal manual engineering. However, we have identified three critical limitations in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	404,209
2306.17162	Can Machines Garden? Systematically Comparing the AlphaGarden vs. Professional Horticulturalists	The AlphaGarden is an automated testbed for indoor polyculture farming which combines a first-order plant simulator, a gantry robot, a seed planting algorithm, plant phenotyping and tracking algorithms, irrigation sensors and algorithms, and custom pruning tools and algorithms. In this paper, we systematically compare ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	376,611
1109.5490	A General Framework for the Optimization of Energy Harvesting Communication Systems with Battery Imperfections	Energy harvesting has emerged as a powerful technology for complementing current battery-powered communication systems in order to extend their lifetime. In this paper a general framework is introduced for the optimization of communication systems in which the transmitter is able to harvest energy from its environment....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,328
1309.7910	A Simple Proof of Maxwell Saturation for Coupled Scalar Recursions	Low-density parity-check (LDPC) convolutional codes (or spatially-coupled codes) were recently shown to approach capacity on the binary erasure channel (BEC) and binary-input memoryless symmetric channels. The mechanism behind this spectacular performance is now called threshold saturation via spatial coupling. This ne...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	27,431
2403.10642	Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs	Existing work in scientific machine learning (SciML) has shown that data-driven learning of solution operators can provide a fast approximate alternative to classical numerical partial differential equation (PDE) solvers. Of these, Neural Operators (NOs) have emerged as particularly promising. We observe that several u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	438,284
2412.17532	Exploring Dynamic Novel View Synthesis Technologies for Cinematography	Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and Gaussian Splatting (GS). These methods model real 3D scenes, enabling the creation of new shots that are challenging to capture in the real ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,012
2307.03910	A Survey of Spiking Neural Network Accelerator on FPGA	Due to the ability to implement customized topology, FPGA is increasingly used to deploy SNNs in both embedded and high-performance applications. In this paper, we survey state-of-the-art SNN implementations and their applications on FPGA. We collect the recent widely-used spiking neuron models, network structures, and...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	378,203
2007.06968	Deep composition of tensor-trains using squared inverse Rosenblatt transports	Characterising intractable high-dimensional random variables is one of the fundamental challenges in stochastic computation. The recent surge of transport maps offers a mathematical foundation and new insights for tackling this challenge by coupling intractable random variables with tractable reference random variables...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	187,191
1901.02662	Deep Semantic Multimodal Hashing Network for Scalable Image-Text and Video-Text Retrievals	Hashing has been widely applied to multimodal retrieval on large-scale multimedia data due to its efficiency in computation and storage. In this article, we propose a novel deep semantic multimodal hashing network (DSMHN) for scalable image-text and video-text retrieval. The proposed deep hashing framework leverages 2-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	118,257
2411.12876	Puppet-CNN: Input-Adaptive Convolutional Neural Networks with Model Compression using Ordinary Differential Equation	Convolutional Neural Network (CNN) has been applied to more and more scenarios due to its excellent performance in many machine learning tasks, especially with deep and complex structures. However, as the network goes deeper, more parameters need to be stored and optimized. Besides, almost all common CNN models adopt "...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	509,579
2203.07853	Concentration Properties of Random Codes	This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to its expectation -- the typical error exponent. For high rates, the result is a co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	285,586
2205.12407	Convolutional Neural Processes for Inpainting Satellite Images	The widespread availability of satellite images has allowed researchers to model complex systems such as disease dynamics. However, many satellite images have missing values due to measurement defects, which render them unusable without data imputation. For example, the scanline corrector for the LANDSAT 7 satellite br...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	298,518
2401.09555	Improving Classification Performance With Human Feedback: Label a few, we label the rest	In the realm of artificial intelligence, where a vast majority of data is unstructured, obtaining substantial amounts of labeled data to train supervised machine learning models poses a significant challenge. To address this, we delve into few-shot and active learning, where are goal is to improve AI models with human ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	422,303
2009.04253	Structured Equilibria for Dynamic Games with Asymmetric Information and Dependent Types	We consider a dynamic game with asymmetric information where each player observes privately a noisy version of a (hidden) state of the world V, resulting in dependent private observations. We study structured perfect Bayesian equilibria that use private beliefs in their strategies as sufficient statistics for summarizi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	194,998
2405.20721	ContextGS: Compact 3D Gaussian Splatting with Anchor Level Context Model	Recently, 3D Gaussian Splatting (3DGS) has become a promising framework for novel view synthesis, offering fast rendering speeds and high fidelity. However, the large number of Gaussians and their associated attributes require effective compression techniques. Existing methods primarily compress neural Gaussians indivi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	459,491
2411.10406	How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits	In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	508,620
2308.07641	Ternary Singular Value Decomposition as a Better Parameterized Form in Linear Mapping	We present a simple yet novel parameterized form of linear mapping to achieves remarkable network compression performance: a pseudo SVD called Ternary SVD (TSVD). Unlike vanilla SVD, TSVD limits the $U$ and $V$ matrices in SVD to ternary matrices form in $\{\pm 1, 0\}$. This means that instead of using the expensive ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	385,594
2210.05709	Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers	Multilingual transformer-based models demonstrate remarkable zero and few-shot transfer across languages by learning and reusing language-agnostic features. However, as a fixed-size model acquires more languages, its performance across all languages degrades, a phenomenon termed interference. Often attributed to limite...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	322,965
2205.10683	Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy	Large convolutional neural networks (CNN) can be difficult to train in the differentially private (DP) regime, since the optimization algorithms require a computationally expensive operation, known as the per-sample gradient clipping. We propose an efficient and scalable implementation of this clipping on convolutional...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	297,814
1906.04798	Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference	In this work, we propose to quantize all parts of standard classification networks and replace the activation-weight--multiply step with a simple table-based lookup. This approach results in networks that are free of floating-point operations and free of multiplications, suitable for direct FPGA and ASIC implementation...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	134,839
2210.17520	Fully Adaptive Composition for Gaussian Differential Privacy	We show that Gaussian Differential Privacy, a variant of differential privacy tailored to the analysis of Gaussian noise addition, composes gracefully even in the presence of a fully adaptive analyst. Such an analyst selects mechanisms (to be run on a sensitive data set) and their privacy budgets adaptively, that is, b...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	327,719
2407.19271	Sewer Image Super-Resolution with Depth Priors and Its Lightweight Network	The Quick-view (QV) technique serves as a primary method for detecting defects within sewerage systems. However, the effectiveness of QV is impeded by the limited visual range of its hardware, resulting in suboptimal image quality for distant portions of the sewer network. Image super-resolution is an effective way to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,712
2305.09293	Out-of-Distribution Detection for Adaptive Computer Vision	It is well known that computer vision can be unreliable when faced with previously unseen imaging conditions. This paper proposes a method to adapt camera parameters according to a normalizing flow-based out-of-distibution detector. A small-scale study is conducted which shows that adapting camera parameters according ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	364,589
2404.19597	TuBA: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning	The implications of backdoor attacks on English-centric large language models (LLMs) have been widely examined - such attacks can be achieved by embedding malicious behaviors during training and activated under specific conditions that trigger malicious outputs. Despite the increasing support for multilingual capabilit...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	450,705
2302.06601	Multiple Instance Learning with Trainable Decision Tree Ensembles	A new random forest based model for solving the Multiple Instance Learning (MIL) problem under small tabular data, called Soft Tree Ensemble MIL (STE-MIL), is proposed. A new type of soft decision trees is considered, which is similar to the well-known soft oblique trees, but with a smaller number of trainable paramete...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	345,471
2104.01241	TreeToaster: Towards an IVM-Optimized Compiler	A compiler's optimizer operates over abstract syntax trees (ASTs), continuously applying rewrite rules to replace subtrees of the AST with more efficient ones. Especially on large source repositories, even simply finding opportunities for a rewrite can be expensive, as optimizer traverses the AST naively. In this paper...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	228,275
2502.13777	Herglotz-NET: Implicit Neural Representation of Spherical Data with Harmonic Positional Encoding	Representing and processing data in spherical domains presents unique challenges, primarily due to the curvature of the domain, which complicates the application of classical Euclidean techniques. Implicit neural representations (INRs) have emerged as a promising alternative for high-fidelity data representation; howev...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	535,514

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