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
1406.2293	Using Gossips to Spread Information: Theory and Evidence from a Randomized Controlled Trial	Is it possible to identify individuals who are highly central in a community without gathering any network information, simply by asking a few people? If we use people's nominees as seeds for a diffusion process, will it be successful? We explore these questions theoretically, via surveys, and via field experiments. We...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	33,734
1912.02605	Towards Understanding Residual and Dilated Dense Neural Networks via Convolutional Sparse Coding	Convolutional neural network (CNN) and its variants have led to many state-of-art results in various fields. However, a clear theoretical understanding about them is still lacking. Recently, multi-layer convolutional sparse coding (ML-CSC) has been proposed and proved to equal such simply stacked networks (plain networ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	156,390
2301.13340	Affinity Uncertainty-based Hard Negative Mining in Graph Contrastive Learning	Hard negative mining has shown effective in enhancing self-supervised contrastive learning (CL) on diverse data types, including graph CL (GCL). The existing hardness-aware CL methods typically treat negative instances that are most similar to the anchor instance as hard negatives, which helps improve the CL performanc...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,864
1806.10206	Deep Feature Factorization For Concept Discovery	We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned features, where we detect hierarchical cluster structures in feature space. This is visualized as heat m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	101,505
1801.06889	Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers	Deep learning has recently seen rapid development and received significant attention due to its state-of-the-art performance on previously-thought hard problems. However, because of the internal complexity and nonlinear structure of deep neural networks, the underlying decision making processes for why these models are...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	88,697
2110.10568	Inference Graphs for CNN Interpretation	Convolutional neural networks (CNNs) have achieved superior accuracy in many visual related tasks. However, the inference process through intermediate layers is opaque, making it difficult to interpret such networks or develop trust in their operation. We propose to model the network hidden layers activity using probab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	262,199
2312.09532	Grounding for Artificial Intelligence	A core function of intelligence is grounding, which is the process of connecting the natural language and abstract knowledge to the internal representation of the real world in an intelligent being, e.g., a human. Human cognition is grounded in our sensorimotor experiences in the external world and subjective feelings ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	415,769
2409.08285	DIC2CAE: Calculating the stress intensity factors (KI-III) from 2D and stereo displacement fields	Integrating experimental data into simulations is crucial for predicting material behaviour, especially in fracture mechanics. Digital Image Correlation (DIC) provides precise displacement measurements, essential for evaluating strain energy release rates and stress intensity factors (SIF) around cracks. Translating DI...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	487,849
2407.02549	Diffusion Models for Tabular Data Imputation and Synthetic Data Generation	Data imputation and data generation have important applications for many domains, like healthcare and finance, where incomplete or missing data can hinder accurate analysis and decision-making. Diffusion models have emerged as powerful generative models capable of capturing complex data distributions across various dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	469,791
2402.16759	The Door and Drawer Reset Mechanisms: Automated Mechanisms for Testing and Data Collection	Robotic manipulation in human environments is a challenging problem for researchers and industry alike. In particular, opening doors/drawers can be challenging for robots, as the size, shape, actuation and required force is variable. Because of this, it can be difficult to collect large real-world datasets and to bench...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	432,681
1911.07960	The {\alpha}{\mu} Search Algorithm for the Game of Bridge	{\alpha}{\mu} is an anytime heuristic search algorithm for incomplete information games that assumes perfect information for the opponents. {\alpha}{\mu} addresses the strategy fusion and non-locality problems encountered by Perfect Information Monte Carlo sampling. In this paper {\alpha}{\mu} is applied to the game of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	154,030
1403.4175	Approximate Dynamic Programming based on Projection onto the (min,+) subsemimodule	We develop a new Approximate Dynamic Programming (ADP) method for infinite horizon discounted reward Markov Decision Processes (MDP) based on projection onto a subsemimodule. We approximate the value function in terms of a $(\min,+)$ linear combination of a set of basis functions whose $(\min,+)$ linear span constitute...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	31,629
2108.10392	A generalized stacked reinforcement learning method for sampled systems	A common setting of reinforcement learning (RL) is a Markov decision process (MDP) in which the environment is a stochastic discrete-time dynamical system. Whereas MDPs are suitable in such applications as video-games or puzzles, physical systems are time-continuous. A general variant of RL is of digital format, where ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	251,881
2310.01571	Contraction Properties of the Global Workspace Primitive	To push forward the important emerging research field surrounding multi-area recurrent neural networks (RNNs), we expand theoretically and empirically on the provably stable RNNs of RNNs introduced by Kozachkov et al. in "RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks". We prove ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	396,474
2412.11100	DynamicScaler: Seamless and Scalable Video Generation for Panoramic Scenes	The increasing demand for immersive AR/VR applications and spatial intelligence has heightened the need to generate high-quality scene-level and 360{\deg} panoramic video. However, most video diffusion models are constrained by limited resolution and aspect ratio, which restricts their applicability to scene-level dyna...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,257
1811.12695	An Efficient Image Retrieval Based on Fusion of Low-Level Visual Features	Due to an increase in the number of image achieves, Content-Based Image Retrieval (CBIR) has gained attention for research community of computer vision. The image visual contents are represented in a feature space in the form of numerical values that is considered as a feature vector of image. Images belonging to diffe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,074
1901.00049	SiCloPe: Silhouette-Based Clothed People	We introduce a new silhouette-based representation for modeling clothed human bodies using deep generative models. Our method can reconstruct a complete and textured 3D model of a person wearing clothes from a single input picture. Inspired by the visual hull algorithm, our implicit representation uses 2D silhouettes a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,674
2305.01653	Physics-Informed and Data-Driven Discovery of Governing Equations for Complex Phenomena in Heterogeneous Media	Rapid evolution of sensor technology, advances in instrumentation, and progress in devising data-acquisition softwares/hardwares are providing vast amounts of data for various complex phenomena, ranging from those in atomospheric environment, to large-scale porous formations, and biological systems. The tremendous incr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	361,756
1904.12274	Robust subspace clustering by Cauchy loss function	Subspace clustering is a problem of exploring the low-dimensional subspaces of high-dimensional data. State-of-the-arts approaches are designed by following the model of spectral clustering based method. These methods pay much attention to learn the representation matrix to construct a suitable similarity matrix and ov...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,065
2401.11929	Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting	Long-term time series forecasting (LTSF) represents a critical frontier in time series analysis, characterized by extensive input sequences, as opposed to the shorter spans typical of traditional approaches. While longer sequences inherently offer richer information for enhanced predictive precision, prevailing studies...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	423,206
1201.3851	Combinatorial Modelling and Learning with Prediction Markets	Combining models in appropriate ways to achieve high performance is commonly seen in machine learning fields today. Although a large amount of combinatorial models have been created, little attention is drawn to the commons in different models and their connections. A general modelling technique is thus worth studying ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	13,877
1511.03981	Disconnected, fragmented, or united? A trans-disciplinary review of network science	During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,825
1906.08928	Learning Reward Functions by Integrating Human Demonstrations and Preferences	Our goal is to accurately and efficiently learn reward functions for autonomous robots. Current approaches to this problem include inverse reinforcement learning (IRL), which uses expert demonstrations, and preference-based learning, which iteratively queries the user for her preferences between trajectories. In roboti...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	136,016
2004.02249	CondenseUNet: A Memory-Efficient Condensely-Connected Architecture for Bi-ventricular Blood Pool and Myocardium Segmentation	With the advent of Cardiac Cine Magnetic Resonance (CMR) Imaging, there has been a paradigm shift in medical technology, thanks to its capability of imaging different structures within the heart without ionizing radiation. However, it is very challenging to conduct pre-operative planning of minimally invasive cardiac p...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	171,172
2006.08085	Optimal Complexity in Decentralized Training	Decentralization is a promising method of scaling up parallel machine learning systems. In this paper, we provide a tight lower bound on the iteration complexity for such methods in a stochastic non-convex setting. Our lower bound reveals a theoretical gap in known convergence rates of many existing decentralized train...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,058
2203.14169	AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning	Automatic Time Series Forecasting (TSF) model design which aims to help users to efficiently design suitable forecasting model for the given time series data scenarios, is a novel research topic to be urgently solved. In this paper, we propose AutoTS algorithm trying to utilize the existing design skills and design eff...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,906
1908.09362	LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm	Multiclass decomposition splits a multiclass classification problem into a series of independent binary learners and recomposes them by combining their outputs to reconstruct the multiclass classification results. Three widely-used realizations of such decomposition methods are One-Versus-All (OVA), One-Versus-One (OVO...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	142,832
1904.13268	Handwritten Chinese Font Generation with Collaborative Stroke Refinement	Automatic character generation is an appealing solution for new typeface design, especially for Chinese typefaces including over 3700 most commonly-used characters. This task has two main pain points: (i) handwritten characters are usually associated with thin strokes of few information and complex structure which are ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,344
2006.04306	On smooth or 0/1 designs of the fixed-mesh element-based topology optimization	The traditional element-based topology optimization based on material penalization typically aims at a 0/1 design. Our numerical experiments reveal that the compliance of a smooth design is overestimated when material properties of boundary intermediate elements under the fixed-mesh finite element analysis are interpol...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	180,645
2412.07282	HARP: Hesitation-Aware Reframing in Transformer Inference Pass	This paper aims to improve the performance of large language models by addressing the variable computational demands in inference steps, where some tokens require more computational resources than others. We present HARP, a simple modification to "off-the-shelf" Transformer forward pass. Drawing from hesitation and the...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	515,609
1812.10576	Deconfounding Reinforcement Learning in Observational Settings	We propose a general formulation for addressing reinforcement learning (RL) problems in settings with observational data. That is, we consider the problem of learning good policies solely from historical data in which unobserved factors (confounders) affect both observed actions and rewards. Our formulation allows us t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,399
2101.00850	Low Light Image Enhancement via Global and Local Context Modeling	Images captured under low-light conditions manifest poor visibility, lack contrast and color vividness. Compared to conventional approaches, deep convolutional neural networks (CNNs) perform well in enhancing images. However, being solely reliant on confined fixed primitives to model dependencies, existing data-driven ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	214,223
2403.13741	Hyper Strategy Logic	Strategy logic (SL) is a powerful temporal logic that enables strategic reasoning in multi-agent systems. SL supports explicit (first-order) quantification over strategies and provides a logical framework to express many important properties such as Nash equilibria, dominant strategies, etc. While in SL the same strate...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	439,756
2007.12087	Hide-and-Seek Privacy Challenge	The clinical time-series setting poses a unique combination of challenges to data modeling and sharing. Due to the high dimensionality of clinical time series, adequate de-identification to preserve privacy while retaining data utility is difficult to achieve using common de-identification techniques. An innovative app...	false	false	false	false	false	false	true	false	false	false	false	false	true	true	false	false	false	false	188,726
2411.02854	SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception	Spiking Neural Networks (SNNs), with their inherent recurrence, offer an efficient method for processing the asynchronous temporal data generated by Dynamic Vision Sensors (DVS), making them well-suited for event-based vision applications. However, existing SNN accelerators suffer from limitations in adaptability to di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	505,694
2205.10893	Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers	In theorem proving, the task of selecting useful premises from a large library to unlock the proof of a given conjecture is crucially important. This presents a challenge for all theorem provers, especially the ones based on language models, due to their relative inability to reason over huge volumes of premises in tex...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	297,915
1802.04065	Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders	In this paper, we study the ability to make the short-term prediction of the exchange price fluctuations towards the United States dollar for the Bitcoin market. We use the data of realized volatility collected from one of the largest Bitcoin digital trading offices in 2016 and 2017 as well as order information. Experi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,135
1506.07191	Construction of power flow feasibility sets	We develop a new approach for construction of convex analytically simple regions where the AC power flow equations are guaranteed to have a feasible solutions. Construction of these regions is based on efficient semidefinite programming techniques accelerated via sparsity exploiting algorithms. Resulting regions have a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	44,484
1711.08856	Critical Learning Periods in Deep Neural Networks	Similar to humans and animals, deep artificial neural networks exhibit critical periods during which a temporary stimulus deficit can impair the development of a skill. The extent of the impairment depends on the onset and length of the deficit window, as in animal models, and on the size of the neural network. Deficit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,283
2305.12099	Soft Actor-Critic Learning-Based Joint Computing, Pushing, and Caching Framework in MEC Networks	To support future 6G mobile applications, the mobile edge computing (MEC) network needs to be jointly optimized for computing, pushing, and caching to reduce transmission load and computation cost. To achieve this, we propose a framework based on deep reinforcement learning that enables the dynamic orchestration of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	365,837
cs/0307063	An Alternative to RDF-Based Languages for the Representation and Processing of Ontologies in the Semantic Web	This paper describes an approach to the representation and processing of ontologies in the Semantic Web, based on the ICMAUS theory of computation and AI. This approach has strengths that complement those of languages based on the Resource Description Framework (RDF) such as RDF Schema and DAML+OIL. The main benefits o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	537,939
1711.09398	Novel Adaptive Genetic Algorithm Sample Consensus	Random sample consensus (RANSAC) is a successful algorithm in model fitting applications. It is vital to have strong exploration phase when there are an enormous amount of outliers within the dataset. Achieving a proper model is guaranteed by pure exploration strategy of RANSAC. However, finding the optimum result requ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	85,395
2107.07853	A Causal Perspective on Meaningful and Robust Algorithmic Recourse	Algorithmic recourse explanations inform stakeholders on how to act to revert unfavorable predictions. However, in general ML models do not predict well in interventional distributions. Thus, an action that changes the prediction in the desired way may not lead to an improvement of the underlying target. Such recourse ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,549
1805.01389	A stabilized mixed discontinuous Galerkin formulation for double porosity/permeability model	Modeling flow through porous media with multiple pore-networks has now become an active area of research due to recent technological endeavors like geological carbon sequestration and recovery of hydrocarbons from tight rock formations. Herein, we consider the double porosity/permeability (DPP) model, which describes t...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	96,651
2309.09212	RobotPerf: An Open-Source, Vendor-Agnostic, Benchmarking Suite for Evaluating Robotics Computing System Performance	We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its common baseline. The suite encompasses ROS 2 packages covering the full robotics pipeline and integrates two distinct benchmarking approaches: ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	392,515
2309.16599	Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation	Zero-shot translation (ZST), which is generally based on a multilingual neural machine translation model, aims to translate between unseen language pairs in training data. The common practice to guide the zero-shot language mapping during inference is to deliberately insert the source and target language IDs, e.g., <EN...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	395,412
2203.09737	Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation	We propose a semi-supervised learning framework for monocular depth estimation. Compared to existing semi-supervised learning methods, which inherit limitations of both sparse supervised and unsupervised loss functions, we achieve the complementary advantages of both loss functions, by building two separate network bra...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	286,268
2409.14820	Past Meets Present: Creating Historical Analogy with Large Language Models	Historical analogies, which compare known past events with contemporary but unfamiliar events, are important abilities that help people make decisions and understand the world. However, research in applied history suggests that people have difficulty finding appropriate analogies. And previous studies in the AI communi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	490,643
2411.16794	Phase-Informed Tool Segmentation for Manual Small-Incision Cataract Surgery	Cataract surgery is the most common surgical procedure globally, with a disproportionately higher burden in developing countries. While automated surgical video analysis has been explored in general surgery, its application to ophthalmic procedures remains limited. Existing works primarily focus on Phaco cataract surge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,188
2003.05224	3-Survivor: A Rough Terrain Negotiable Teleoperated Mobile Rescue Robot with Passive Control Mechanism	This paper presents the design and integration of 3 Survivor, a rough terrain negotiable teleoperated mobile rescue and service robot. 3 Survivor is an improved version of two previously studied surveillance robots named Sigma 3 and Alpha N. In 3 Survivor, a modified double tracked with caterpillar mechanism is incorpo...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	167,809
1408.2289	Physical Computing With No Clock to Implement the Gaussian Pyramid of SIFT Algorithm	Physical computing is a technology utilizing the nature of electronic devices and circuit topology to cope with computing tasks. In this paper, we propose an active circuit network to implement multi-scale Gaussian filter, which is also called Gaussian Pyramid in image preprocessing. Various kinds of methods have been ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	35,282
2409.13096	Fast decision tree learning solves hard coding-theoretic problems	We connect the problem of properly PAC learning decision trees to the parameterized Nearest Codeword Problem ($k$-NCP). Despite significant effort by the respective communities, algorithmic progress on both problems has been stuck: the fastest known algorithm for the former runs in quasipolynomial time (Ehrenfeucht and...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	489,847
1707.09926	A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames	This paper introduces a framework for super-resolution of scalable video based on compressive sensing and sparse representation of residual frames in reconnaissance and surveillance applications. We exploit efficient compressive sampling and sparse reconstruction algorithms to super-resolve the video sequence with resp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,113
1909.11498	Non-imaging single-pixel sensing with optimized binary modulation	The conventional high-level sensing techniques require high-fidelity images as input to extract target features, which are produced by either complex imaging hardware or high-complexity reconstruction algorithms. In this letter, we propose single-pixel sensing (SPS) that performs high-level sensing directly from couple...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	146,826
1509.05172	Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis	We consider the off-policy evaluation problem in Markov decision processes with function approximation. We propose a generalization of the recently introduced \emph{emphatic temporal differences} (ETD) algorithm \citep{SuttonMW15}, which encompasses the original ETD($\lambda$), as well as several other off-policy evalu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	47,013
2411.15824	Variable-size Symmetry-based Graph Fourier Transforms for image compression	Modern compression systems use linear transformations in their encoding and decoding processes, with transforms providing compact signal representations. While multiple data-dependent transforms for image/video coding can adapt to diverse statistical characteristics, assembling large datasets to learn each transform is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,790
2408.09275	Design and Control of Modular Soft-Rigid Hybrid Manipulators with Self-Contact	Soft robotics focuses on designing robots with highly deformable materials, allowing them to adapt and operate safely and reliably in unstructured and variable environments. While soft robots offer increased compliance over rigid body robots, their payloads are limited, and they consume significant energy when operatin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	481,363
2408.08729	ConcateNet: Dialogue Separation Using Local And Global Feature Concatenation	Dialogue separation involves isolating a dialogue signal from a mixture, such as a movie or a TV program. This can be a necessary step to enable dialogue enhancement for broadcast-related applications. In this paper, ConcateNet for dialogue separation is proposed, which is based on a novel approach for processing local...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	481,127
2406.17363	Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation	This paper describes our system submission to the International Conference on Spoken Language Translation (IWSLT 2024) for Irish-to-English speech translation. We built end-to-end systems based on Whisper, and employed a number of data augmentation techniques, such as speech back-translation and noise augmentation. We ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,543
2103.08317	Boosted Genetic Algorithm using Machine Learning for traffic control optimization	Traffic control optimization is a challenging task for various traffic centers around the world and the majority of existing approaches focus only on developing adaptive methods under normal (recurrent) traffic conditions. Optimizing the control plans when severe incidents occur still remains an open problem, especiall...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	224,872
2112.08217	Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization	Probabilistic forecasting relies on past observations to provide a probability distribution for a future outcome, which is often evaluated against the realization using a scoring rule. Here, we perform probabilistic forecasting with generative neural networks, which parametrize distributions on high-dimensional spaces ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,731
1909.01602	SQuAP-Ont: an Ontology of Software Quality Relational Factors from Financial Systems	Quality, architecture, and process are considered the keystones of software engineering. ISO defines them in three separate standards. However, their interaction has been scarcely studied, so far. The SQuAP model (Software Quality, Architecture, Process) describes twenty-eight main factors that impact on software quali...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	143,953
1212.3139	Identifying Metaphoric Antonyms in a Corpus Analysis of Finance Articles	Using a corpus of 17,000+ financial news reports (involving over 10M words), we perform an analysis of the argument-distributions of the UP and DOWN verbs used to describe movements of indices, stocks and shares. In Study 1 participants identified antonyms of these verbs in a free-response task and a matching task from...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	20,369
1301.6190	Blahut-Arimoto Algorithm and Code Design for Action-Dependent Source Coding Problems	The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient algorithm for numerical computation of the rate-distortion-cost function for this problem is proposed, and a convergence pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	21,390
1908.07599	Learning document embeddings along with their uncertainties	Majority of the text modelling techniques yield only point-estimates of document embeddings and lack in capturing the uncertainty of the estimates. These uncertainties give a notion of how well the embeddings represent a document. We present Bayesian subspace multinomial model (Bayesian SMM), a generative log-linear mo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	142,321
2310.17119	FLEEK: Factual Error Detection and Correction with Evidence Retrieved from External Knowledge	Detecting factual errors in textual information, whether generated by large language models (LLM) or curated by humans, is crucial for making informed decisions. LLMs' inability to attribute their claims to external knowledge and their tendency to hallucinate makes it difficult to rely on their responses. Humans, too, ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	402,993
2403.13653	Learning User Embeddings from Human Gaze for Personalised Saliency Prediction	Reusable embeddings of user behaviour have shown significant performance improvements for the personalised saliency prediction task. However, prior works require explicit user characteristics and preferences as input, which are often difficult to obtain. We present a novel method to extract user embeddings from pairs o...	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	439,717
1703.09772	Particle Filtering for PLCA model with Application to Music Transcription	Automatic Music Transcription (AMT) consists in automatically estimating the notes in an audio recording, through three attributes: onset time, duration and pitch. Probabilistic Latent Component Analysis (PLCA) has become very popular for this task. PLCA is a spectrogram factorization method, able to model a magnitude ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	70,793
1802.06613	Before Name-calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation	Arguing without committing a fallacy is one of the main requirements of an ideal debate. But even when debating rules are strictly enforced and fallacious arguments punished, arguers often lapse into attacking the opponent by an ad hominem argument. As existing research lacks solid empirical investigation of the typolo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	90,715
2308.13395	A Gr\"obner Approach to Dual-Containing Cyclic Left Module $(\theta,\delta)$-Codes over Finite Commutative Frobenius Rings	For a skew polynomial ring $R=A[X;\theta,\delta]$ where $A$ is a commutative Frobenius ring, $\theta$ an endomorphism of $A$ and $\delta$ a $\theta$-derivation of $A$, we consider cyclic left module codes $\mathcal{C}=Rg/Rf\subset R/Rf$ where $g$ is a left and right divisor of $f$ in $R$. In this paper, we derive a par...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	387,902
1409.4391	Direct Sum Theorem for Bounded Round Quantum Communication Complexity	We prove a direct sum theorem for bounded round entanglement-assisted quantum communication complexity. To do so, we use the fully quantum definition for information cost and complexity that we recently introduced, and use both the fact that information is a lower bound on the communication, and the fact that a direct ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	36,069
2312.11097	Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation	The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,443
2311.01995	From Discrete to Continuous Binary Best-Response Dynamics: Discrete Fluctuations Almost Surely Vanish with Population Size	In binary decision-makings, individuals often go for a common or rare action. In the framework of evolutionary game theory, the best-response update rule can be used to model this dichotomy. Those who prefer a common action are called \emph{coordinators}, and those who prefer a rare one are called \emph{anticoordinator...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	405,257
1605.09497	Interdependent Scheduling Games	We propose a model of interdependent scheduling games in which each player controls a set of services that they schedule independently. A player is free to schedule his own services at any time; however, each of these services only begins to accrue reward for the player when all predecessor services, which may or may n...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false	false	true	56,572
2206.00979	Multi-scale Wasserstein Shortest-path Graph Kernels for Graph Classification	Graph kernels are conventional methods for computing graph similarities. However, the existing R-convolution graph kernels cannot resolve both of the two challenges: 1) Comparing graphs at multiple different scales, and 2) Considering the distributions of substructures when computing the kernel matrix. These two challe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	300,318
2409.18394	An Augmented Reality Interface for Teleoperating Robot Manipulators: Reducing Demonstrator Task Load through Digital Twin Control	Acquiring high-quality demonstration data is essential for the success of data-driven methods, such as imitation learning. Existing platforms for providing demonstrations for manipulation tasks often impose significant physical and mental demands on the demonstrator, require additional hardware systems, or necessitate ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	492,232
2406.10741	Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare	The process of identifying human emotion and affective states from speech is known as speech emotion recognition (SER). This is based on the observation that tone and pitch in the voice frequently convey underlying emotion. Speech recognition includes the ability to recognize emotions, which is becoming increasingly po...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	464,535
2407.04130	Towards Automating Text Annotation: A Case Study on Semantic Proximity Annotation using GPT-4	This paper explores using GPT-3.5 and GPT-4 to automate the data annotation process with automatic prompting techniques. The main aim of this paper is to reuse human annotation guidelines along with some annotated data to design automatic prompts for LLMs, focusing on the semantic proximity annotation task. Automatic p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	470,440
1609.01152	Well-Posedness and Output Regulation for Implicit Time-Varying Evolution Variational Inequalities	A class of evolution variational inequalities (EVIs), which comprises ordinary differential equations (ODEs) coupled with variational inequalities (VIs) associated with time-varying set-valued mappings, is proposed in this paper. We first study the conditions for existence and uniqueness of solutions. The central idea ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	60,561
2404.11826	AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence	As the integration of large language models into daily life is on the rise, there is a clear gap in benchmarks for advising on subjective and personal dilemmas. To address this, we introduce AdvisorQA, the first benchmark developed to assess LLMs' capability in offering advice for deeply personalized concerns, utilizin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	447,628
1505.00870	An $O(n\log(n))$ Algorithm for Projecting Onto the Ordered Weighted $\ell_1$ Norm Ball	The ordered weighted $\ell_1$ (OWL) norm is a newly developed generalization of the Octogonal Shrinkage and Clustering Algorithm for Regression (OSCAR) norm. This norm has desirable statistical properties and can be used to perform simultaneous clustering and regression. In this paper, we show how to compute the projec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	42,782
2502.01456	Process Reinforcement through Implicit Rewards	Dense process rewards have proven a more effective alternative to the sparse outcome-level rewards in the inference-time scaling of large language models (LLMs), particularly in tasks requiring complex multi-step reasoning. While dense rewards also offer an appealing choice for the reinforcement learning (RL) of LLMs s...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	529,862
2202.03103	Combining Deep Learning and Reasoning for Address Detection in Unstructured Text Documents	Extracting information from unstructured text documents is a demanding task, since these documents can have a broad variety of different layouts and a non-trivial reading order, like it is the case for multi-column documents or nested tables. Additionally, many business documents are received in paper form, meaning tha...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	279,078
1403.2654	Flying Insect Classification with Inexpensive Sensors	The ability to use inexpensive, noninvasive sensors to accurately classify flying insects would have significant implications for entomological research, and allow for the development of many useful applications in vector control for both medical and agricultural entomology. Given this, the last sixty years have seen m...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	31,498
2202.13234	Safe Exploration for Efficient Policy Evaluation and Comparison	High-quality data plays a central role in ensuring the accuracy of policy evaluation. This paper initiates the study of efficient and safe data collection for bandit policy evaluation. We formulate the problem and investigate its several representative variants. For each variant, we analyze its statistical properties, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,533
2010.13962	Task-Aware Neural Architecture Search	The design of handcrafted neural networks requires a lot of time and resources. Recent techniques in Neural Architecture Search (NAS) have proven to be competitive or better than traditional handcrafted design, although they require domain knowledge and have generally used limited search spaces. In this paper, we propo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	203,299
1907.10226	Movement science needs different pose tracking algorithms	Over the last decade, computer science has made progress towards extracting body pose from single camera photographs or videos. This promises to enable movement science to detect disease, quantify movement performance, and take the science out of the lab into the real world. However, current pose tracking algorithms fa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	139,565
1001.3122	Erasure entropies and Gibbs measures	Recently Verdu and Weissman introduced erasure entropies, which are meant to measure the information carried by one or more symbols given all of the remaining symbols in the realization of the random process or field. A natural relation to Gibbs measures has also been observed. In his short note we study this relation ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,435
2302.11824	MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions	Transformer based models have provided significant performance improvements in monaural speech separation. However, there is still a performance gap compared to a recent proposed upper bound. The major limitation of the current dual-path Transformer models is the inefficient modelling of long-range elemental interactio...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	347,328
2106.02016	Semantic-WER: A Unified Metric for the Evaluation of ASR Transcript for End Usability	Recent advances in supervised, semi-supervised and self-supervised deep learning algorithms have shown significant improvement in the performance of automatic speech recognition(ASR) systems. The state-of-the-art systems have achieved a word error rate (WER) less than 5%. However, in the past, researchers have argued t...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,697
1604.01566	Achievable Rates for Gaussian Degraded Relay Channels with Non-Vanishing Error Probabilities	This paper revisits the Gaussian degraded relay channel, where the link that carries information from the source to the destination is a physically degraded version of the link that carries information from the source to the relay. The source and the relay are subject to expected power constraints. The $\varepsilon$-ca...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,213
2410.14268	MoDification: Mixture of Depths Made Easy	Long-context efficiency has recently become a trending topic in serving large language models (LLMs). And mixture of depths (MoD) is proposed as a perfect fit to bring down both latency and memory. In this paper, however, we discover that MoD can barely transform existing LLMs without costly training over an extensive ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	499,964
2306.03988	Learn the Force We Can: Enabling Sparse Motion Control in Multi-Object Video Generation	We propose a novel unsupervised method to autoregressively generate videos from a single frame and a sparse motion input. Our trained model can generate unseen realistic object-to-object interactions. Although our model has never been given the explicit segmentation and motion of each object in the scene during trainin...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	371,557
2002.04205	Fine-grained Uncertainty Modeling in Neural Networks	Existing uncertainty modeling approaches try to detect an out-of-distribution point from the in-distribution dataset. We extend this argument to detect finer-grained uncertainty that distinguishes between (a). certain points, (b). uncertain points but within the data distribution, and (c). out-of-distribution points. O...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	163,543
2311.10782	A BERT based Ensemble Approach for Sentiment Classification of Customer Reviews and its Application to Nudge Marketing in e-Commerce	According to the literature, Product reviews are an important source of information for customers to support their buying decision. Product reviews improve customer trust and loyalty. Reviews help customers in understanding what other customers think about a particular product and helps in driving purchase decisions. T...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	408,654
2304.01235	How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of Documents	We introduce a new dataset named WikiVitals which contains a large graph of 48k mutually referred Wikipedia articles classified into 32 categories and connected by 2.3M edges. Our aim is to rigorously evaluate the contributions of three distinct sources of information to the label prediction in a semi-supervised node c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,992
2004.13177	PowerModelsRestoration.jl: An Open-Source Framework for Exploring Power Network Restoration Algorithms	With the escalating frequency of extreme grid disturbances, such as natural disasters, comes an increasing need for efficient recovery plans. Algorithms for optimal power restoration play an important role in developing such plans, but also give rise to challenging mixed-integer nonlinear optimization problems, where t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	174,469
1504.00481	Data Dissemination Problem in Wireless Networks	In this work, we formulate and study a data dissemination problem, which can be viewed as a generalization of the index coding problem and of the data exchange problem to networks with an arbitrary topology. We define $r$-solvable networks, in which data dissemination can be achieved in $r > 0$ communications rounds. W...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,708
2212.12616	Assessing thermal imagery integration into object detection methods on ground-based and air-based collection platforms	Object detection models commonly deployed on uncrewed aerial systems (UAS) focus on identifying objects in the visible spectrum using Red-Green-Blue (RGB) imagery. However, there is growing interest in fusing RGB with thermal long wave infrared (LWIR) images to increase the performance of object detection machine learn...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	338,074
2010.03821	Clustering Analysis of Interactive Learning Activities Based on Improved BIRCH Algorithm	Group tendency is a research branch of computer assisted learning. The construction of good learning behavior is of great significance to learners' learning process and learning effect, and is the key basis of data-driven education decision-making. Clustering analysis is an effective method for the study of group tende...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,542

Subsets and Splits

No community queries yet

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