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
1206.6847	Identifying the Relevant Nodes Without Learning the Model	We propose a method to identify all the nodes that are relevant to compute all the conditional probability distributions for a given set of nodes. Our method is simple, effcient, consistent, and does not require learning a Bayesian network first. Therefore, our method can be applied to high-dimensional databases, e.g. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	17,073
2305.12452	Advancing Referring Expression Segmentation Beyond Single Image	Referring Expression Segmentation (RES) is a widely explored multi-modal task, which endeavors to segment the pre-existing object within a single image with a given linguistic expression. However, in broader real-world scenarios, it is not always possible to determine if the described object exists in a specific image....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	366,008
2206.07898	Multimodal Dialogue State Tracking	Designed for tracking user goals in dialogues, a dialogue state tracker is an essential component in a dialogue system. However, the research of dialogue state tracking has largely been limited to unimodality, in which slots and slot values are limited by knowledge domains (e.g. restaurant domain with slots of restaura...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	302,929
2409.11235	SLAck: Semantic, Location, and Appearance Aware Open-Vocabulary Tracking	Open-vocabulary Multiple Object Tracking (MOT) aims to generalize trackers to novel categories not in the training set. Currently, the best-performing methods are mainly based on pure appearance matching. Due to the complexity of motion patterns in the large-vocabulary scenarios and unstable classification of the novel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,066
2111.10933	Decentralized Upper Confidence Bound Algorithms for Homogeneous Multi-Agent Multi-Armed Bandits	This paper studies a decentralized homogeneous multi-armed bandit problem in a multi-agent network. The problem is simultaneously solved by $N$ agents assuming they face a common set of $M$ arms and share the same arms' reward distributions. Each agent can receive information only from its neighbors, where the neighbor...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	267,491
1804.09820	A Nonlinear Spectral Method for Core--Periphery Detection in Networks	We derive and analyse a new iterative algorithm for detecting network core--periphery structure. Using techniques in nonlinear Perron-Frobenius theory, we prove global convergence to the unique solution of a relaxed version of a natural discrete optimization problem. On sparse networks, the cost of each iteration scale...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	96,044
2208.03712	TPM: Transition Probability Matrix -- Graph Structural Feature based Embedding	In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The information obtained from random walks is converted to anonymous walks to extra...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	311,877
2402.01741	Development and Testing of a Novel Large Language Model-Based Clinical Decision Support Systems for Medication Safety in 12 Clinical Specialties	Importance: We introduce a novel Retrieval Augmented Generation (RAG)-Large Language Model (LLM) framework as a Clinical Decision Support Systems (CDSS) to support safe medication prescription. Objective: To evaluate the efficacy of LLM-based CDSS in correctly identifying medication errors in different patient case v...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	426,188
2112.02998	A PubMedBERT-based Classifier with Data Augmentation Strategy for Detecting Medication Mentions in Tweets	As a major social media platform, Twitter publishes a large number of user-generated text (tweets) on a daily basis. Mining such data can be used to address important social, public health, and emergency management issues that are infeasible through other means. An essential step in many text mining pipelines is named ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	270,040
1908.01994	Comprehensive Fuzzy Turing Machines, An Evolution to the Concept of Finite State Machine Control	The Turing machine is an abstract concept of a computing device which introduced new models for computation. The idea of Fuzzy algorithms defined by Zadeh and Lee was followed by introducing Fuzzy Turing Machine (FTM) to create a platform for a new fuzzy computation model. Then, in his investigations on its computation...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	140,905
2412.16083	Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation	The increasing demand for privacy-preserving data analytics in finance necessitates solutions for synthetic data generation that rigorously uphold privacy standards. We introduce DP-Fed-FinDiff framework, a novel integration of Differential Privacy, Federated Learning and Denoising Diffusion Probabilistic Models design...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	519,349
2409.05503	Fast Computation for the Forest Matrix of an Evolving Graph	The forest matrix plays a crucial role in network science, opinion dynamics, and machine learning, offering deep insights into the structure of and dynamics on networks. In this paper, we study the problem of querying entries of the forest matrix in evolving graphs, which more accurately represent the dynamic nature of...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	486,799
1910.01923	Layout-Graph Reasoning for Fashion Landmark Detection	Detecting dense landmarks for diverse clothes, as a fundamental technique for clothes analysis, has attracted increasing research attention due to its huge application potential. However, due to the lack of modeling underlying semantic layout constraints among landmarks, prior works often detect ambiguous and structure...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,087
1705.08317	A Cloud-based Service for Real-Time Performance Evaluation of NoSQL Databases	We have created a cloud-based service that allows the end users to run tests on multiple different databases to find which databases are most suitable for their project. From our research, we could not find another application that enables the user to test several databases to gauge the difference between them. This ap...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	73,997
1211.2367	IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying on Large Graphs	We study the problem of computing shortest path or distance between two query vertices in a graph, which has numerous important applications. Quite a number of indexes have been proposed to answer such distance queries. However, all of these indexes can only process graphs of size barely up to 1 million vertices, which...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	19,675
2305.11255	Reasoning Implicit Sentiment with Chain-of-Thought Prompting	While sentiment analysis systems try to determine the sentiment polarities of given targets based on the key opinion expressions in input texts, in implicit sentiment analysis (ISA) the opinion cues come in an implicit and obscure manner. Thus detecting implicit sentiment requires the common-sense and multi-hop reasoni...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	365,446
1905.11664	OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks	Channel pruning can significantly accelerate and compress deep neural networks. Many channel pruning works utilize structured sparsity regularization to zero out all the weights in some channels and automatically obtain structure-sparse network in training stage. However, these methods apply structured sparsity regular...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	132,503
2407.12637	Toward INT4 Fixed-Point Training via Exploring Quantization Error for Gradients	Network quantization generally converts full-precision weights and/or activations into low-bit fixed-point values in order to accelerate an inference process. Recent approaches to network quantization further discretize the gradients into low-bit fixed-point values, enabling an efficient training. They typically set a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,013
2207.06032	Abnormality Detection and Localization Schemes using Molecular Communication Systems: A Survey	Abnormality detection and localization (ADL) have been studied widely in wireless sensor networks (WSNs) literature, where the sensors use electromagnetic waves for communication. Molecular communication (MC) has been introduced as an alternative approach for ADL in particular areas such as healthcare, being able to ta...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	307,747
1701.06545	Exponent Function for Stationary Memoryless Channels with Input Cost at Rates above the Capacity	We consider the stationaly memoryless channels with input cost. We prove that for transmission rates above the capacity the correct probability of decoding tends to zero exponentially as the block length $n$ of codes tends to infinity. In the case where both of channel input and output sets are finite, we determine the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,155
2402.11173	How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization	We provide a simple and flexible framework for designing differentially private algorithms to find approximate stationary points of non-convex loss functions. Our framework is based on using a private approximate risk minimizer to "warm start" another private algorithm for finding stationary points. We use this framewo...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	430,267
1009.2221	Performance Bounds and Design Criteria for Estimating Finite Rate of Innovation Signals	In this paper, we consider the problem of estimating finite rate of innovation (FRI) signals from noisy measurements, and specifically analyze the interaction between FRI techniques and the underlying sampling methods. We first obtain a fundamental limit on the estimation accuracy attainable regardless of the sampling ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,531
2411.02788	When to Localize? A Risk-Constrained Reinforcement Learning Approach	In a standard navigation pipeline, a robot localizes at every time step to lower navigational errors. However, in some scenarios, a robot needs to selectively localize when it is expensive to obtain observations. For example, an underwater robot surfacing to localize too often hinders it from searching for critical ite...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	505,659
1702.08101	Solutions for Practice-oriented Requirements for Optimal Path Planning for the AUV "SLOCUM Glider"	This paper presents a few important practiceoriented requirements for optimal path planning for the AUV "SLOCUM Glider" as well as solutions using fast graph basedalgorithms. These algorithms build upon the TVE (time-varying environment) search algorithm. The experience with this algorithm, requirements of real mission...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	68,920
2304.03917	MC-MLP:Multiple Coordinate Frames in all-MLP Architecture for Vision	In deep learning, Multi-Layer Perceptrons (MLPs) have once again garnered attention from researchers. This paper introduces MC-MLP, a general MLP-like backbone for computer vision that is composed of a series of fully-connected (FC) layers. In MC-MLP, we propose that the same semantic information has varying levels of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,992
2502.00461	On Multiquantum Bits, Segre Embeddings and Coxeter Chambers	This work explores the interplay between quantum information theory, algebraic geometry, and number theory, with a particular focus on multiqubit systems, their entanglement structure, and their classification via geometric embeddings. The Segre embedding, a fundamental construction in algebraic geometry, provides an a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	529,393
2404.17357	Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Model	In clinical practice, tri-modal medical image fusion, compared to the existing dual-modal technique, can provide a more comprehensive view of the lesions, aiding physicians in evaluating the disease's shape, location, and biological activity. However, due to the limitations of imaging equipment and considerations for p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,830
2001.04861	Fairness in Learning-Based Sequential Decision Algorithms: A Survey	Algorithmic fairness in decision-making has been studied extensively in static settings where one-shot decisions are made on tasks such as classification. However, in practice most decision-making processes are of a sequential nature, where decisions made in the past may have an impact on future data. This is particula...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	160,381
1910.11477	Phase Retrieval of Low-Rank Matrices by Anchored Regression	We study the low-rank phase retrieval problem, where we try to recover a $d_1\times d_2$ low-rank matrix from a series of phaseless linear measurements. This is a fourth-order inverse problem, as we are trying to recover factors of matrix that have been put through a quadratic nonlinearity after being multiplied togeth...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	150,787
2203.15323	Improving Persian Relation Extraction Models by Data Augmentation	Relation extraction that is the task of predicting semantic relation type between entities in a sentence or document is an important task in natural language processing. Although there are many researches and datasets for English, Persian suffers from sufficient researches and comprehensive datasets. The only available...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	288,345
2108.11357	ProoFVer: Natural Logic Theorem Proving for Fact Verification	Fact verification systems typically rely on neural network classifiers for veracity prediction which lack explainability. This paper proposes ProoFVer, which uses a seq2seq model to generate natural logic-based inferences as proofs. These proofs consist of lexical mutations between spans in the claim and the evidence r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	252,164
2312.16755	Graph Neural Networks for Antisocial Behavior Detection on Twitter	Social media resurgence of antisocial behavior has exerted a downward spiral on stereotypical beliefs, and hateful comments towards individuals and social groups, as well as false or distorted news. The advances in graph neural networks employed on massive quantities of graph-structured data raise high hopes for the fu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	418,495
2501.04272	On weight and variance uncertainty in neural networks for regression tasks	We consider the problem of weight uncertainty proposed by [Blundell et al. (2015). Weight uncertainty in neural network. In International conference on machine learning, 1613-1622, PMLR.] in neural networks {(NNs)} specialized for regression tasks. {We further} investigate the effect of variance uncertainty in {their m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,156
2203.04738	Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences	Parallelizing Gated Recurrent Unit (GRU) networks is a challenging task, as the training procedure of GRU is inherently sequential. Prior efforts to parallelize GRU have largely focused on conventional parallelization strategies such as data-parallel and model-parallel training algorithms. However, when the given seque...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	284,580
2112.03267	Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding	Mobile devices are indispensable sources of big data. Federated learning (FL) has a great potential in exploiting these private data by exchanging locally trained models instead of their raw data. However, mobile devices are often energy limited and wirelessly connected, and FL cannot cope flexibly with their heterogen...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	270,143
1710.10386	Dual Skipping Networks	Inspired by the recent neuroscience studies on the left-right asymmetry of the human brain in processing low and high spatial frequency information, this paper introduces a dual skipping network which carries out coarse-to-fine object categorization. Such a network has two branches to simultaneously deal with both coar...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	83,369
1303.6711	An intelligent approach towards automatic shape modeling and object extraction from satellite images using cellular automata based algorithm	Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given enough consideration. In this paper, we propose a frame work for accurate detection...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	23,284
2408.00217	Load Balancing in Federated Learning	Federated Learning (FL) is a decentralized machine learning framework that enables learning from data distributed across multiple remote devices, enhancing communication efficiency and data privacy. Due to limited communication resources, a scheduling policy is often applied to select a subset of devices for participat...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	477,746
1603.03083	A Decentralized Mechanism for Computing Competitive Equilibria in Deregulated Electricity Markets	With the increased level of distributed generation and demand response comes the need for associated mechanisms that can perform well in the face of increasingly complex deregulated energy market structures. Using Lagrangian duality theory, we develop a decentralized market mechanism that ensures that, under the guidan...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	53,072
2501.01806	TRG-planner: Traversal Risk Graph-Based Path Planning in Unstructured Environments for Safe and Efficient Navigation	Unstructured environments such as mountains, caves, construction sites, or disaster areas are challenging for autonomous navigation because of terrain irregularities. In particular, it is crucial to plan a path to avoid risky terrain and reach the goal quickly and safely. In this paper, we propose a method for safe and...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	522,220
2104.03123	Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection	This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems. An example of neural architecture search, DARTS operates upon a continuous, differentiable search space which enables both the architecture and parameters to be o...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,981
2410.17744	Learning Versatile Skills with Curriculum Masking	Masked prediction has emerged as a promising pretraining paradigm in offline reinforcement learning (RL) due to its versatile masking schemes, enabling flexible inference across various downstream tasks with a unified model. Despite the versatility of masked prediction, it remains unclear how to balance the learning of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	501,597
1803.11034	Automatic Generation of Optimal Reductions of Distributions	A reduction of a source distribution is a collection of smaller sized distributions that are collectively equivalent to the source distribution with respect to the property of decomposability. That is, an arbitrary language is decomposable with respect to the source distribution if and only if it is decomposable with r...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	93,808
2106.14144	Learning-based Framework for Sensor Fault-Tolerant Building HVAC Control with Model-assisted Learning	As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort and reducing energy consumption. These HVAC systems in smart buildings rely on real-time sensor readings, which in practice often suffer from...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	243,306
2209.02986	Shifting Perspective to See Difference: A Novel Multi-View Method for Skeleton based Action Recognition	Skeleton-based human action recognition is a longstanding challenge due to its complex dynamics. Some fine-grain details of the dynamics play a vital role in classification. The existing work largely focuses on designing incremental neural networks with more complicated adjacent matrices to capture the details of joint...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	316,364
1509.03602	DeepSat - A Learning framework for Satellite Imagery	Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent in satellite data, most of the current object classification approaches are not suitable for handling satellite datasets. The progress of sat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	46,850
2002.12142	Energy Resolved Neutron Imaging for Strain Reconstruction using the Finite Element Method	A pulsed neutron imaging technique is used to reconstruct the residual strain within a polycrystalline material from Bragg edge strain images. This technique offers the possibility of a nondestructive analysis of strain fields with a high spatial resolution. A finite element approach is used to reconstruct the strain u...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	165,937
2412.09668	Vision-Language Models Represent Darker-Skinned Black Individuals as More Homogeneous than Lighter-Skinned Black Individuals	Vision-Language Models (VLMs) combine Large Language Model (LLM) capabilities with image processing, enabling tasks like image captioning and text-to-image generation. Yet concerns persist about their potential to amplify human-like biases, including skin tone bias. Skin tone bias, where darker-skinned individuals face...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,595
2106.01144	Towards Emotional Support Dialog Systems	Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats. Following reasonable procedures and using various support skills can help to effectively provide support. However, due to the lack of a well-designed task and corpora...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,404
2501.15915	Parametric Retrieval Augmented Generation	Retrieval-augmented generation (RAG) techniques have emerged as a promising solution to enhance the reliability of large language models (LLMs) by addressing issues like hallucinations, outdated knowledge, and domain adaptation. In particular, existing RAG methods append relevant documents retrieved from external corpu...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	527,759
2411.00039	Linear Chain Transformation: Expanding Optimization Dynamics for Fine-Tuning Large Language Models	Fine-tuning large language models (LLMs) has become essential for adapting pretrained models to specific downstream tasks. In this paper, we propose Linear Chain Transformation (LinChain), a novel approach that introduces a sequence of linear transformations during fine-tuning to enrich optimization dynamics. By incorp...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	504,409
2311.08354	Hierarchical Experience-informed Navigation for Multi-modal Quadrupedal Rebar Grid Traversal	This study focuses on a layered, experience-based, multi-modal contact planning framework for agile quadrupedal locomotion over a constrained rebar environment. To this end, our hierarchical planner incorporates locomotion-specific modules into the high-level contact sequence planner and solves kinodynamically-aware tr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	407,688
2007.11189	Predicting Job-Hopping Motive of Candidates Using Answers to Open-ended Interview Questions	A significant proportion of voluntary employee turnover includes people who frequently move from job to job, known as job-hopping. Our work shows that language used in responding to interview questions on past behaviour and situational judgement is predictive of job-hopping motive as measured by the Job-Hopping Motives...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	188,490
2412.09466	Distributional Reinforcement Learning based Integrated Decision Making and Control for Autonomous Surface Vehicles	With the growing demands for Autonomous Surface Vehicles (ASVs) in recent years, the number of ASVs being deployed for various maritime missions is expected to increase rapidly in the near future. However, it is still challenging for ASVs to perform sensor-based autonomous navigation in obstacle-filled and congested wa...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	516,494
1904.08397	SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning	Real-world optimization problems often have expensive objective functions in terms of cost and time. It is desirable to find near-optimal solutions with very few function evaluations. Surrogate-assisted optimizers tend to reduce the required number of function evaluations by replacing the real function with an efficien...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	128,046
1401.7369	Linear Codes are Optimal for Index-Coding Instances with Five or Fewer Receivers	We study zero-error unicast index-coding instances, where each receiver must perfectly decode its requested message set, and the message sets requested by any two receivers do not overlap. We show that for all these instances with up to five receivers, linear index codes are optimal. Although this class contains 9847 n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	30,447
math/0701131	Compressed Sensing and Redundant Dictionaries	This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, which is a composition of a random matrix of certain type and a deterministic dictionary, has small restricted isometry constants. Thus, signals ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,734
2403.10992	On extended perfect codes	We consider extended $1$-perfect codes in Hamming graphs $H(n,q)$. Such nontrivial codes are known only when $n=2^k$, $k\geq 1$, $q=2$, or $n=q+2$, $q=2^m$, $m\geq 1$. Recently, Bespalov proved nonexistence of extended $1$-perfect codes for $q=3$, $4$, $n>q+2$. In this work, we characterize all positive integers $n$, $...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	438,469
2405.05662	Approximate Dec-POMDP Solving Using Multi-Agent A*	We present an A-based algorithm to compute policies for finite-horizon Dec-POMDPs. Our goal is to sacrifice optimality in favor of scalability for larger horizons. The main ingredients of our approach are (1) using clustered sliding window memory, (2) pruning the A search tree, and (3) using novel A* heuristics. Our ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	453,008
1406.2785	A New Class of Multiple-rate Codes Based on Block Markov Superposition Transmission	Hadamard transform~(HT) as over the binary field provides a natural way to implement multiple-rate codes~(referred to as {\em HT-coset codes}), where the code length $N=2^p$ is fixed but the code dimension $K$ can be varied from $1$ to $N-1$ by adjusting the set of frozen bits. The HT-coset codes, including Reed-Muller...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,787
2106.12142	IQ-Learn: Inverse soft-Q Learning for Imitation	In many sequential decision-making problems (e.g., robotics control, game playing, sequential prediction), human or expert data is available containing useful information about the task. However, imitation learning (IL) from a small amount of expert data can be challenging in high-dimensional environments with complex ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	242,634
2204.01198	Antenna Impedance Estimation at MIMO Receivers	This paper considers antenna impedance estimation based on training sequences at MIMO receivers. The goal is to firstly leverage extensive resources available in most wireless systems for channel estimation to estimate antenna impedance in real-time. We assume the receiver switches its impedance in a predetermined fash...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	289,530
2312.16109	fMPI: Fast Novel View Synthesis in the Wild with Layered Scene Representations	In this study, we propose two novel input processing paradigms for novel view synthesis (NVS) methods based on layered scene representations that significantly improve their runtime without compromising quality. Our approach identifies and mitigates the two most time-consuming aspects of traditional pipelines: building...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	418,267
2302.10631	FedST: Secure Federated Shapelet Transformation for Time Series Classification	This paper explores how to build a shapelet-based time series classification (TSC) model in the federated learning (FL) scenario, that is, using more data from multiple owners without actually sharing the data. We propose FedST, a novel federated TSC framework extended from a centralized shapelet transformation method....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	346,874
2006.06244	CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks	Despite the recent success of text detection and recognition methods, existing evaluation metrics fail to provide a fair and reliable comparison among those methods. In addition, there exists no end-to-end evaluation metric that takes characteristics of OCR tasks into account. Previous end-to-end metric contains cascad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	181,360
2305.00278	Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected	Meta AI Research has recently released SAM (Segment Anything Model) which is trained on a large segmentation dataset of over 1 billion masks. As a foundation model in the field of computer vision, SAM (Segment Anything Model) has gained attention for its impressive performance in generic object segmentation. Despite it...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	361,278
1706.10197	Improving Speech Related Facial Action Unit Recognition by Audiovisual Information Fusion	It is challenging to recognize facial action unit (AU) from spontaneous facial displays, especially when they are accompanied by speech. The major reason is that the information is extracted from a single source, i.e., the visual channel, in the current practice. However, facial activity is highly correlated with voice...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,256
2204.05369	Learning Implicit Priors for Motion Optimization	In this paper, we focus on the problem of integrating Energy-based Models (EBM) as guiding priors for motion optimization. EBMs are a set of neural networks that can represent expressive probability density distributions in terms of a Gibbs distribution parameterized by a suitable energy function. Due to their implicit...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	290,998
2111.11289	Environment-Aware Beam Selection for IRS-Aided Communication with Channel Knowledge Map	Intelligent reflecting surface (IRS)-aided communication is a promising technology for beyond 5G (B5G) systems, to reconfigure the radio environment proactively. However, IRS-aided communication in practice requires efficient channel estimation or passive beam training, whose overhead and complexity increase drasticall...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	267,613
1606.07767	Sampling-based Gradient Regularization for Capturing Long-Term Dependencies in Recurrent Neural Networks	Vanishing (and exploding) gradients effect is a common problem for recurrent neural networks with nonlinear activation functions which use backpropagation method for calculation of derivatives. Deep feedforward neural networks with many hidden layers also suffer from this effect. In this paper we propose a novel univer...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	57,775
1908.03830	Supervised Negative Binomial Classifier for Probabilistic Record Linkage	Motivated by the need of the linking records across various databases, we propose a novel graphical model based classifier that uses a mixture of Poisson distributions with latent variables. The idea is to derive insight into each pair of hypothesis records that match by inferring its underlying latent rate of error us...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	141,330
2004.14788	Character-Level Translation with Self-attention	We explore the suitability of self-attention models for character-level neural machine translation. We test the standard transformer model, as well as a novel variant in which the encoder block combines information from nearby characters using convolutions. We perform extensive experiments on WMT and UN datasets, testi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	175,006
cs/0211004	The DLV System for Knowledge Representation and Reasoning	This paper presents the DLV system, which is widely considered the state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free disjunctive logic programs (also known as disjunctive datalog),...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	537,716
1911.04096	UW-MARL: Multi-Agent Reinforcement Learning for Underwater Adaptive Sampling using Autonomous Vehicles	Near-real-time water-quality monitoring in uncertain environments such as rivers, lakes, and water reservoirs of different variables is critical to protect the aquatic life and to prevent further propagation of the potential pollution in the water. In order to measure the physical values in a region of interest, adapti...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	152,889
2210.09822	Two low differentially uniform power permutations over odd characteristic finite fields: APN and differentially $4$-uniform functions	Permutation polynomials over finite fields are fundamental objects as they are used in various theoretical and practical applications in cryptography, coding theory, combinatorial design, and related topics. This family of polynomials constitutes an active research area in which advances are being made constantly. In p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	324,683
1504.04003	Anatomy-specific classification of medical images using deep convolutional nets	Automated classification of human anatomy is an important prerequisite for many computer-aided diagnosis systems. The spatial complexity and variability of anatomy throughout the human body makes classification difficult. "Deep learning" methods such as convolutional networks (ConvNets) outperform other state-of-the-ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	42,092
2404.00623	Variational Autoencoders for exteroceptive perception in reinforcement learning-based collision avoidance	Modern control systems are increasingly turning to machine learning algorithms to augment their performance and adaptability. Within this context, Deep Reinforcement Learning (DRL) has emerged as a promising control framework, particularly in the domain of marine transportation. Its potential for autonomous marine appl...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	443,031
2209.07163	Morphology-Aware Interactive Keypoint Estimation	Diagnosis based on medical images, such as X-ray images, often involves manual annotation of anatomical keypoints. However, this process involves significant human efforts and can thus be a bottleneck in the diagnostic process. To fully automate this procedure, deep-learning-based methods have been widely proposed and ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	317,650
1702.08130	Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems	In this paper, we develop a low-complexity channel estimation for hybrid millimeter wave (mmWave) systems, where the number of radio frequency (RF) chains is much less than the number of antennas equipped at each transceiver. The proposed channel estimation algorithm aims to estimate the strongest angle-of-arrivals (Ao...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,926
2306.04098	Phoenix: A Federated Generative Diffusion Model	Generative AI has made impressive strides in enabling users to create diverse and realistic visual content such as images, videos, and audio. However, training generative models on large centralized datasets can pose challenges in terms of data privacy, security, and accessibility. Federated learning (FL) is an approac...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	371,602
2401.08584	Nahid: AI-based Algorithm for operating fully-automatic surgery	In this paper, for the first time, a method is presented that can provide a fully automated surgery based on software and computer vision techniques. Then, the advantages and challenges of computerization of medical surgery are examined. Finally, the surgery related to isolated ovarian endometriosis disease has been ex...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	true	false	false	421,947
2009.03005	Towards an Interoperable Data Protocol Aimed at Linking the Fashion Industry with AI Companies	The fashion industry is looking forward to use artificial intelligence technologies to enhance their processes, services, and applications. Although the amount of fashion data currently in use is increasing, there is a large gap in data exchange between the fashion industry and the related AI companies, not to mention ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	194,718
2311.07711	Histopathologic Cancer Detection	Early diagnosis of the cancer cells is necessary for making an effective treatment plan and for the health and safety of a patient. Nowadays, doctors usually use a histological grade that pathologists determine by performing a semi-quantitative analysis of the histopathological and cytological features of hematoxylin-e...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	407,442
2107.07229	Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task	The recent state-of-the-art natural language understanding (NLU) systems often behave unpredictably, failing on simpler reasoning examples. Despite this, there has been limited focus on quantifying progress towards systems with more predictable behavior. We think that reasoning capability-wise behavioral summary is a s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	246,353
1205.3504	A Note on Extending Taylor's Power Law for Characterizing Human Microbial Communities: Inspiration from Comparative Studies on the Distribution Patterns of Insects and Galaxies, and as a Case Study for Medical Ecology	Many natural patterns, such as the distributions of blood particles in a blood sample, proteins on cell surfaces, biological populations in their habitat, galaxies in the universe, the sequence of human genes, and the fitness in evolutionary computing, have been found to follow power law. Taylor's power law (Taylor 196...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	16,029
1810.00046	Estimation-Based Model Predictive Control for Automatic Crosswind Stabilization of Hybrid Aerial Vehicles	In this paper, we study the control design of an automatic crosswind stabilization system for a novel, buoyantly-assisted aerial transportation vehicle. This vehicle has several advantages over other aircraft including the ability to take-off and land in very short distances and without the need for roads or runways. D...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	109,079
2205.13272	FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devices	IoT devices suffer from resource limitations, such as processor, RAM, and disc storage. These limitations become more evident when handling demanding applications, such as deep learning, well-known for their heavy computational requirements. A case in point is robot pose estimation, an application that predicts the cri...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	298,871
2409.04056	Refining Wikidata Taxonomy using Large Language Models	Due to its collaborative nature, Wikidata is known to have a complex taxonomy, with recurrent issues like the ambiguity between instances and classes, the inaccuracy of some taxonomic paths, the presence of cycles, and the high level of redundancy across classes. Manual efforts to clean up this taxonomy are time-consum...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	486,275
2111.15046	A Secure Key Sharing Algorithm Exploiting Phase Reciprocity in Wireless Channels	This article presents a secure key exchange algorithm that exploits reciprocity in wireless channels to share a secret key between two nodes $A$ and $B$. Reciprocity implies that the channel phases in the links $A\rightarrow B$ and $B\rightarrow A$ are the same. A number of such reciprocal phase values are measured at ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	268,787
2312.11084	Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects	Connected and automated vehicles (CAVs) are considered a potential solution for future transportation challenges, aiming to develop systems that are efficient, safe, and environmentally friendly. However, CAV control presents significant challenges due to the complexity of interconnectivity and coordination required am...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	416,441
1703.00168	Modular Representation of Layered Neural Networks	Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its inte...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	69,122
2402.08878	Distributed Secret Securing in Discrete-Event Systems	In this paper, we study a security problem of protecting secrets in distributed systems. Specifically, we employ discrete-event systems to describe the structure and behaviour of distributed systems, in which global secret information is separated into pieces and stored in local component agents. The goal is to prevent...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	429,276
1702.03253	D4M 3.0	The D4M tool is used by hundreds of researchers to perform complex analytics on unstructured data. Over the past few years, the D4M toolbox has evolved to support connectivity with a variety of database engines, graph analytics in the Apache Accumulo database, and an implementation using the Julia programming language....	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	68,099
2204.02350	Information-Theoretic Policy Learning from Partial Observations with Fully Informed Decision Makers	In this work we formulate and treat an extension of the Imitation from Observations problem. Imitation from Observations is a generalisation of the well-known Imitation Learning problem where state-only demonstrations are considered. In our treatment we extend the scope of Imitation from Observations to feature-only de...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	289,910
1406.3454	The Degrees-of-Freedom of Multi-way Device-to-Device Communications is Limited by 2	A 3-user device-to-device (D2D) communications scenario is studied where each user wants to send and receive a message from each other user. This scenario resembles a 3-way communication channel. The capacity of this channel is unknown in general. In this paper, a sum-capacity upper bound that characterizes the degrees...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,848
1807.11560	Efficient Gauss-Newton-Krylov momentum conservation constrained PDE-LDDMM using the band-limited vector field parameterization	The class of non-rigid registration methods proposed in the framework of PDE-constrained Large Deformation Diffeomorphic Metric Mapping is a particularly interesting family of physically meaningful diffeomorphic registration methods. PDE-constrained LDDMM methods are formulated as constrained variational problems, wher...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	104,195
1709.01421	Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks	Automatic analysis of the video is one of most complex problems in the fields of computer vision and machine learning. A significant part of this research deals with (human) activity recognition (HAR) since humans, and the activities that they perform, generate most of the video semantics. Video-based HAR has applicati...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	80,073
2008.03346	Generative Adversarial Network for Radar Signal Generation	A major obstacle in radar based methods for concealed object detection on humans and seamless integration into security and access control system is the difficulty in collecting high quality radar signal data. Generative adversarial networks (GAN) have shown promise in data generation application in the fields of image...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	190,868
2111.00278	A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles	Emergency vehicles (EMVs) play a critical role in a city's response to time-critical events such as medical emergencies and fire outbreaks. The existing approaches to reduce EMV travel time employ route optimization and traffic signal pre-emption without accounting for the coupling between route these two subproblems. ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	264,167
1807.10194	Linkage between piecewise constant Mumford-Shah model and ROF model and its virtue in image segmentation	The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fatemi (ROF) model are two important variational models in image segmentation and image restoration, respectively. In this paper, we explore a linkage between these models. We prove that for the two-phase segmentation problem a partial minimizer of th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	103,892

Subsets and Splits

No community queries yet

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