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
2110.15232	Guided Evolution for Neural Architecture Search	Neural Architecture Search (NAS) methods have been successfully applied to image tasks with excellent results. However, NAS methods are often complex and tend to converge to local minima as soon as generated architectures seem to yield good results. In this paper, we propose G-EA, a novel approach for guided evolutiona...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	263,812
2307.11445	An Extended Nonlinear Stability Assessment Methodology For Type-4 Wind Turbines via Time Reversal Trajectory	As the integration of renewable energy generation increases and as conventional generation is phased out, there is a gradual decline in the grid's strength and resilience at the connection point of wind turbines (WTs). Previous studies have shown that traditional grid-following controlled converters exhibit deteriorati...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	380,909
2410.04989	Conditional Variational Autoencoders for Probabilistic Pose Regression	Robots rely on visual relocalization to estimate their pose from camera images when they lose track. One of the challenges in visual relocalization is repetitive structures in the operation environment of the robot. This calls for probabilistic methods that support multiple hypotheses for robot's pose. We propose such ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	495,522
2407.07794	Reinforcement Learning of Adaptive Acquisition Policies for Inverse Problems	A promising way to mitigate the expensive process of obtaining a high-dimensional signal is to acquire a limited number of low-dimensional measurements and solve an under-determined inverse problem by utilizing the structural prior about the signal. In this paper, we focus on adaptive acquisition schemes to save furthe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	471,906
2109.01949	Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment	Self-supervised learning provides an opportunity to explore unlabeled chest X-rays and their associated free-text reports accumulated in clinical routine without manual supervision. This paper proposes a Joint Image Text Representation Learning Network (JoImTeRNet) for pre-training on chest X-ray images and their radio...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	253,588
2409.19492	MedHalu: Hallucinations in Responses to Healthcare Queries by Large Language Models	The remarkable capabilities of large language models (LLMs) in language understanding and generation have not rendered them immune to hallucinations. LLMs can still generate plausible-sounding but factually incorrect or fabricated information. As LLM-empowered chatbots become popular, laypeople may frequently ask healt...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	492,705
2401.17699	Unified Physical-Digital Face Attack Detection	Face Recognition (FR) systems can suffer from physical (i.e., print photo) and digital (i.e., DeepFake) attacks. However, previous related work rarely considers both situations at the same time. This implies the deployment of multiple models and thus more computational burden. The main reasons for this lack of an integ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	425,289
2410.06819	Dynamic Neural Potential Field: Online Trajectory Optimization in Presence of Moving Obstacles	We address a task of local trajectory planning for the mobile robot in the presence of static and dynamic obstacles. Local trajectory is obtained as a numerical solution of the Model Predictive Control (MPC) problem. Collision avoidance may be provided by adding repulsive potential of the obstacles to the cost function...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	496,361
2005.09412	MaskFace: multi-task face and landmark detector	Currently in the domain of facial analysis single task approaches for face detection and landmark localization dominate. In this paper we draw attention to multi-task models solving both tasks simultaneously. We present a highly accurate model for face and landmark detection. The method, called MaskFace, extends previo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,926
2308.01479	Investigating Reinforcement Learning for Communication Strategies in a Task-Initiative Setting	Many conversational domains require the system to present nuanced information to users. Such systems must follow up what they say to address clarification questions and repair misunderstandings. In this work, we explore this interactive strategy in a referential communication task. Using simulation, we analyze the comm...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	383,262
2409.10583	Reinforcement Learning with Quasi-Hyperbolic Discounting	Reinforcement learning has traditionally been studied with exponential discounting or the average reward setup, mainly due to their mathematical tractability. However, such frameworks fall short of accurately capturing human behavior, which has a bias towards immediate gratification. Quasi-Hyperbolic (QH) discounting i...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	488,811
1701.06687	On the Average Locality of Locally Repairable Codes	A linear block code with dimension $k$, length $n$, and minimum distance $d$ is called a locally repairable code (LRC) with locality $r$ if it can retrieve any coded symbol by at most $r$ other coded symbols. LRCs have been recently proposed and used in practice in distributed storage systems (DSSs) such as Windows Azu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,180
2204.07075	Learning and controlling the source-filter representation of speech with a variational autoencoder	Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are p...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	291,557
1508.01171	Meta-MapReduce: A Technique for Reducing Communication in MapReduce Computations	MapReduce has proven to be one of the most useful paradigms in the revolution of distributed computing, where cloud services and cluster computing become the standard venue for computing. The federation of cloud and big data activities is the next challenge where MapReduce should be modified to avoid (big) data migrati...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	45,762
2101.04535	Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning	Differentially private (DP) machine learning allows us to train models on private data while limiting data leakage. DP formalizes this data leakage through a cryptographic game, where an adversary must predict if a model was trained on a dataset D, or a dataset D' that differs in just one example.If observing the train...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	215,171
2008.09169	Development of a Novel Computational Model for Evaluating Fall Risk in Patient Room Design	Objectives: The aims of this study are to identify factors in physical environments that contribute to patient falls in hospitals and to propose a computational model to evaluate patient room designs. Background: The existing fall risk assessment tools have an acceptable level of sensitivity and specificity, however,...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	192,633
2102.05771	Predicting Customer Lifetime Values -- ecommerce use case	Predicting customer future purchases and lifetime value is a key metrics for managing marketing campaigns and optimizing marketing spend. This task is specifically challenging when the relationships between the customer and the firm are of a noncontractual nature and therefore the future purchases need to be predicted ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,538
2101.11787	Joint Transmission Scheme and Coded Content Placement in Cluster-centric UAV-aided Cellular Networks	Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote working and telemedicine has significantly increased. In cellular networks, incorporation of Unmanned Aerial Vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing L...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	217,389
2412.02247	Development and Performance of a Static Pluviometer System	As the frequency and severity of climate-related events such as droughts, floods, and water scarcity continue to escalate, accurate rainfall monitoring becomes increasingly critical. This paper covers various industry methods of measuring rainfall as well as our own ground pluviometer system. Our system consists of an ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	513,452
1903.00069	Vine Robots: Design, Teleoperation, and Deployment for Navigation and Exploration	A new class of continuum robots has recently been explored, characterized by tip extension, significant length change, and directional control. Here, we call this class of robots "vine robots," due to their similar behavior to plants with the growth habit of trailing. Due to their growth-based movement, vine robots are...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	122,927
1911.06181	Adversarial Transformations for Semi-Supervised Learning	We propose a Regularization framework based on Adversarial Transformations (RAT) for semi-supervised learning. RAT is designed to enhance robustness of the output distribution of class prediction for a given data against input perturbation. RAT is an extension of Virtual Adversarial Training (VAT) in such a way that RA...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	153,470
2004.11437	Efficient Neural Architecture for Text-to-Image Synthesis	Text-to-image synthesis is the task of generating images from text descriptions. Image generation, by itself, is a challenging task. When we combine image generation and text, we bring complexity to a new level: we need to combine data from two different modalities. Most of recent works in text-to-image synthesis follo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,904
2108.12851	Lower Bounds for the MMSE via Neural Network Estimation and Their Applications to Privacy	The minimum mean-square error (MMSE) achievable by optimal estimation of a random variable $Y\in\mathbb{R}$ given another random variable $X\in\mathbb{R}^{d}$ is of much interest in a variety of statistical settings. In the context of estimation-theoretic privacy, the MMSE has been proposed as an information leakage me...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	252,628
2403.00326	DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion	Infrared-visible object detection aims to achieve robust even full-day object detection by fusing the complementary information of infrared and visible images. However, highly dynamically variable complementary characteristics and commonly existing modality misalignment make the fusion of complementary information diff...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,944
2303.06263	Quantum Machine Learning Implementations: Proposals and Experiments	This article gives an overview and a perspective of recent theoretical proposals and their experimental implementations in the field of quantum machine learning. Without an aim to being exhaustive, the article reviews specific high-impact topics such as quantum reinforcement learning, quantum autoencoders, and quantum ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,764
2409.05521	Harmonic Reasoning in Large Language Models	Large Language Models (LLMs) are becoming very popular and are used for many different purposes, including creative tasks in the arts. However, these models sometimes have trouble with specific reasoning tasks, especially those that involve logical thinking and counting. This paper looks at how well LLMs understand and...	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	486,803
2010.08908	Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds	We propose a general scheme for solving convex and non-convex optimization problems on manifolds. The central idea is that, by adding a multiple of the squared retraction distance to the objective function in question, we "convexify" the objective function and solve a series of convex sub-problems in the optimization p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	201,347
1912.01730	Distance-Based Learning from Errors for Confidence Calibration	Deep neural networks (DNNs) are poorly calibrated when trained in conventional ways. To improve confidence calibration of DNNs, we propose a novel training method, distance-based learning from errors (DBLE). DBLE bases its confidence estimation on distances in the representation space. In DBLE, we first adapt prototypi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,159
2105.11698	Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting	This paper explores the task of Difficulty-Controllable Question Generation (DCQG), which aims at generating questions with required difficulty levels. Previous research on this task mainly defines the difficulty of a question as whether it can be correctly answered by a Question Answering (QA) system, lacking interpre...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	236,793
1602.00351	Adaptive Subgradient Methods for Online AUC Maximization	Learning for maximizing AUC performance is an important research problem in Machine Learning and Artificial Intelligence. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	51,564
1611.08927	High-Multiplicity Election Problems	The computational study of elections generally assumes that the preferences of the electorate come in as a list of votes. Depending on the context, it may be much more natural to represent the list succinctly, as the distinct votes of the electorate and their counts, i.e., high-multiplicity representation. We consider ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	64,584
2201.02466	On The Decoding Error Weight of One or Two Deletion Channels	This paper tackles two problems that are relevant to coding for insertions and deletions. These problems are motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm, a word is transmitted over some fixed number of identical independent channels and the g...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	274,552
2307.09569	Design of Whisker-Inspired Sensors for Multi-Directional Hydrodynamic Sensing	This research develops a novel sensor for aquatic robots inspired by the whiskers of harbor seals. This sensor can detect the movement of water, offering valuable data on speed, currents, barriers, and water disturbance. It employs a mechano-magnetic system, separating the whisker-like drag part from the electronic sec...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	380,212
2007.13306	Public Sentiment Toward Solar Energy: Opinion Mining of Twitter Using a Transformer-Based Language Model	Public acceptance and support for renewable energy are important determinants of renewable energy policies and market conditions. This paper examines public sentiment toward solar energy in the United States using data from Twitter, a micro-blogging platform in which people post messages, known as tweets. We filtered t...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	189,090
1909.04745	Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text	Our goal is to better comprehend procedural text, e.g., a paragraph about photosynthesis, by not only predicting what happens, but why some actions need to happen before others. Our approach builds on a prior process comprehension framework for predicting actions' effects, to also identify subsequent steps that those e...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	144,878
2402.09795	An advanced data fabric architecture leveraging homomorphic encryption and federated learning	Data fabric is an automated and AI-driven data fusion approach to accomplish data management unification without moving data to a centralized location for solving complex data problems. In a Federated learning architecture, the global model is trained based on the learned parameters of several local models that elimina...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	false	429,687
1807.10201	A Style-Aware Content Loss for Real-time HD Style Transfer	Recently, style transfer has received a lot of attention. While much of this research has aimed at speeding up processing, the approaches are still lacking from a principled, art historical standpoint: a style is more than just a single image or an artist, but previous work is limited to only a single instance of a sty...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	103,893
1905.11474	Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction	Although "black box" models such as Artificial Neural Networks, Support Vector Machines, and Ensemble Approaches continue to show superior performance in many disciplines, their adoption in the sensitive disciplines (e.g., finance, healthcare) is questionable due to the lack of interpretability and explainability of th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	132,429
2101.11605	Bottleneck Transformers for Visual Recognition	We present BoTNet, a conceptually simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, object detection and instance segmentation. By just replacing the spatial convolutions with global self-attention in the final three bottleneck ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	217,336
2108.05569	Agnostic Online Learning and Excellent Sets	We use algorithmic methods from online learning to revisit a key idea from the interaction of model theory and combinatorics, the existence of large "indivisible" sets, called "$\epsilon$-excellent," in $k$-edge stable graphs (equivalently, Littlestone classes). These sets arise in the Stable Regularity Lemma, a theore...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	250,340
1709.05443	A Kinodynamic Aggressive Trajectory Planner For Narrow Passages	Planning a path for a nonholonomic robot is a challenging topic in motion planning and it becomes more difficult when the desired path contains narrow passages. This kind of scenario can arise, for instance, when quadcopters search a collapsed building after a natural disaster. Choosing the quadcopter as the target pla...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	80,871
1810.13069	Dynamic Assortment Optimization with Changing Contextual Information	In this paper, we study the dynamic assortment optimization problem under a finite selling season of length $T$. At each time period, the seller offers an arriving customer an assortment of substitutable products under a cardinality constraint, and the customer makes the purchase among offered products according to a d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,896
1809.08862	Characterization of Biologically Relevant Network Structures form Time-series Data	High-throughput data acquisition in synthetic biology leads to an abundance of data that need to be processed and aggregated into useful biological models. Building dynamical models based on this wealth of data is of paramount importance to understand and optimize designs of synthetic biology constructs. However, build...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	108,610
1912.12978	Image retrieval approach based on local texture information derived from predefined patterns and spatial domain information	With the development of Information technology and communication, a large part of the databases is dedicated to images and videos. Thus retrieving images related to a query image from a large database has become an important area of research in computer vision. Until now, there are various methods of image retrieval th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,979
2109.04223	KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational Graphs	Incorporating factual knowledge into pre-trained language models (PLM) such as BERT is an emerging trend in recent NLP studies. However, most of the existing methods combine the external knowledge integration module with a modified pre-training loss and re-implement the pre-training process on the large-scale corpus. R...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	254,320
2207.11117	Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks	Fifth-Generation (5G) networks have a potential to accelerate power system transition to a flexible, softwarized, data-driven, and intelligent grid. With their evolving support for Machine Learning (ML)/Artificial Intelligence (AI) functions, 5G networks are expected to enable novel data-centric Smart Grid (SG) service...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	309,503
2411.12726	LazyDINO: Fast, scalable, and efficiently amortized Bayesian inversion via structure-exploiting and surrogate-driven measure transport	We present LazyDINO, a transport map variational inference method for fast, scalable, and efficiently amortized solutions of high-dimensional nonlinear Bayesian inverse problems with expensive parameter-to-observable (PtO) maps. Our method consists of an offline phase in which we construct a derivative-informed neural ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	509,513
2205.01845	Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds	Discovering latent topics from text corpora has been studied for decades. Many existing topic models adopt a fully unsupervised setting, and their discovered topics may not cater to users' particular interests due to their inability of leveraging user guidance. Although there exist seed-guided topic discovery approache...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	294,736
2212.02906	A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection	Artificial intelligence is creating one of the biggest revolution across technology driven application fields. For the finance sector, it offers many opportunities for significant market innovation and yet broad adoption of AI systems heavily relies on our trust in their outputs. Trust in technology is enabled by under...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,927
2211.13495	Few-shot Object Detection with Refined Contrastive Learning	Due to the scarcity of sampling data in reality, few-shot object detection (FSOD) has drawn more and more attention because of its ability to quickly train new detection concepts with less data. However, there are still failure identifications due to the difficulty in distinguishing confusable classes. We also notice t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	332,496
2010.02975	Supervised Seeded Iterated Learning for Interactive Language Learning	Language drift has been one of the major obstacles to train language models through interaction. When word-based conversational agents are trained towards completing a task, they tend to invent their language rather than leveraging natural language. In recent literature, two general methods partially counter this pheno...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,220
1811.05542	Extractive Summary as Discrete Latent Variables	In this paper, we compare various methods to compress a text using a neural model. We find that extracting tokens as latent variables significantly outperforms the state-of-the-art discrete latent variable models such as VQ-VAE. Furthermore, we compare various extractive compression schemes. There are two best-performi...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	113,334
1512.02357	Towards the Application of Linear Programming Methods For Multi-Camera Pose Estimation	We presented a separation based optimization algorithm which, rather than optimization the entire variables altogether, This would allow us to employ: 1) a class of nonlinear functions with three variables and 2) a convex quadratic multivariable polynomial, for minimization of reprojection error. Neglecting the inversi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	49,929
2006.12155	Neural Cellular Automata Manifold	Very recently, the Neural Cellular Automata (NCA) has been proposed to simulate the morphogenesis process with deep networks. NCA learns to grow an image starting from a fixed single pixel. In this work, we show that the neural network (NN) architecture of the NCA can be encapsulated in a larger NN. This allows us to p...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	183,494
2301.04652	Estimate Deformation Capacity of Non-Ductile RC Shear Walls using Explainable Boosting Machine	Machine learning is becoming increasingly prevalent for tackling challenges in earthquake engineering and providing fairly reliable and accurate predictions. However, it is mostly unclear how decisions are made because machine learning models are generally highly sophisticated, resulting in opaque black-box models. Mac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	340,133
2308.12480	Lightweight Materialization for Fast Dashboards Over Joins	Dashboards are vital in modern business intelligence tools, providing non-technical users with an interface to access comprehensive business data. With the rise of cloud technology, there is an increased number of data sources to provide enriched contexts for various analytical tasks, leading to a demand for interactiv...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	387,548
2312.00164	Towards Accurate Differential Diagnosis with Large Language Models	An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces powered by Large Language Models (LLMs) present new opportunities to both as...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	411,936
1612.01905	The Classical Limit of Entropic Quantum Dynamics	The framework of entropic dynamics (ED) allows one to derive quantum mechanics as an application of entropic inference. In this work we derive the classical limit of quantum mechanics in the context of ED. Our goal is to find conditions so that the center of mass (CM) of a system of N particles behaves as a classical p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,160
1805.02203	Dynamic and Static Topic Model for Analyzing Time-Series Document Collections	For extracting meaningful topics from texts, their structures should be considered properly. In this paper, we aim to analyze structured time-series documents such as a collection of news articles and a series of scientific papers, wherein topics evolve along time depending on multiple topics in the past and are also r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	96,803
1403.0957	On the Symmetric $K$-user Interference Channels with Limited Feedback	In this paper, we develop achievability schemes for symmetric $K$-user interference channels with a rate-limited feedback from each receiver to the corresponding transmitter. We study this problem under two different channel models: the linear deterministic model, and the Gaussian model. For the deterministic model, th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,345
1607.02060	Detecting Communities under Differential Privacy	Complex networks usually expose community structure with groups of nodes sharing many links with the other nodes in the same group and relatively few with the nodes of the rest. This feature captures valuable information about the organization and even the evolution of the network. Over the last decade, a great number ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	58,300
1710.06846	Kolmogorov Complexity and Information Content	In this paper, we revisit a central concept in Kolmogorov complexity in which one would equate program-size complexity with information content. Despite the fact that Kolmogorov complexity has been widely accepted as an objective measure of the information content of a string, it has been the subject of many criticisms...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	82,839
2003.06259	Taylor Expansion Policy Optimization	In this work, we investigate the application of Taylor expansions in reinforcement learning. In particular, we propose Taylor expansion policy optimization, a policy optimization formalism that generalizes prior work (e.g., TRPO) as a first-order special case. We also show that Taylor expansions intimately relate to of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	168,067
2203.01735	Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification	RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images. In this work, we propose a novel modality-adaptive mixup and invariant decomposition (MID) approach for RGB-infrared person re-id...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,498
1206.2123	Extending Term Suggestion with Author Names	Term suggestion or recommendation modules can help users to formulate their queries by mapping their personal vocabularies onto the specialized vocabulary of a digital library. While we examined actual user queries of the social sciences digital library Sowiport we could see that nearly one third of the users were expl...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	16,419
2212.02361	Dominance as an Indicator of Rapport and Learning in Human-Agent Communication	Power dynamics in human-human communication can impact rapport-building and learning gains, but little is known about how power impacts human-agent communication. In this paper, we examine dominance behavior in utterances between middle-school students and a teachable robot as they work through math problems, as coded ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	334,763
1211.5283	DNF-AF Selection Two-Way Relaying	Error propagation and noise propagation at the relay node would highly degrade system performance in two-way relay networks. In this paper, we introduce DNF-AF selection two-way relaying scheme which aims to avoid error propagation and mitigate noise propagation. If the relay successfully decodes the exclusive or (XOR)...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,878
2006.07207	On topology optimization of large deformation contact-aided shape morphing compliant mechanisms	A topology optimization approach for designing large deformation contact-aided shape morphing compliant mechanisms is presented. Such mechanisms can be used in varying operating conditions. Design domains are described by regular hexagonal elements. Negative circular masks are employed to perform dual task, i.e., to de...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	181,719
2106.14439	Prior-Induced Information Alignment for Image Matting	Image matting is an ill-posed problem that aims to estimate the opacity of foreground pixels in an image. However, most existing deep learning-based methods still suffer from the coarse-grained details. In general, these algorithms are incapable of felicitously distinguishing the degree of exploration between determini...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,412
2006.16591	A Novel Bistatic Joint Radar-Communication System in Multi-path Environments	Radar detection and communication can be operated simultaneously in joint radar-communication (JRC) system. In this paper, we propose a bistatic JRC system which is applicable in multi-path environments. Basing on a novel joint waveform, a joint detection process is designed for both target detection and channel estima...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	184,853
0911.3422	Co-occurrence Matrices and their Applications in Information Science: Extending ACA to the Web Environment	Co-occurrence matrices, such as co-citation, co-word, and co-link matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of this data. The underlying problem, in our opinion, involved understanding the nature of various types of matr...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	4,968
2306.12685	Rethinking the Backward Propagation for Adversarial Transferability	Transfer-based attacks generate adversarial examples on the surrogate model, which can mislead other black-box models without access, making it promising to attack real-world applications. Recently, several works have been proposed to boost adversarial transferability, in which the surrogate model is usually overlooked...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,030
2203.06498	The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning	Recent arguments that machine learning (ML) is facing a reproducibility and replication crisis suggest that some published claims in ML research cannot be taken at face value. These concerns inspire analogies to the replication crisis affecting the social and medical sciences. They also inspire calls for the integratio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	285,139
2012.07816	Enabling Collaborative Data Science Development with the Ballet Framework	While the open-source software development model has led to successful large-scale collaborations in building software systems, data science projects are frequently developed by individuals or small teams. We describe challenges to scaling data science collaborations and present a conceptual framework and ML programmin...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	211,584
1509.06767	Localisation of directional scale-discretised wavelets on the sphere	Scale-discretised wavelets yield a directional wavelet framework on the sphere where a signal can be probed not only in scale and position but also in orientation. Furthermore, a signal can be synthesised from its wavelet coefficients exactly, in theory and practice (to machine precision). Scale-discretised wavelets ar...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,188
2208.10919	Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images	Federated learning (FL) is a decentralized method enabling hospitals to collaboratively learn a model without sharing private patient data for training. In FL, participant hospitals periodically exchange training results rather than training samples with a central server. However, having access to model parameters or g...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	314,250
2309.00125	Pure Differential Privacy for Functional Summaries via a Laplace-like Process	Many existing mechanisms to achieve differential privacy (DP) on infinite-dimensional functional summaries often involve embedding these summaries into finite-dimensional subspaces and applying traditional DP techniques. Such mechanisms generally treat each dimension uniformly and struggle with complex, structured summ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	389,199
2411.07641	Top-$n\sigma$: Not All Logits Are You Need	Large language models (LLMs) typically employ greedy decoding or low-temperature sampling for reasoning tasks, reflecting a perceived trade-off between diversity and accuracy. We challenge this convention by introducing top-$n\sigma$, a novel sampling method that operates directly on pre-softmax logits by leveraging a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	507,627
2401.18018	On Prompt-Driven Safeguarding for Large Language Models	Prepending model inputs with safety prompts is a common practice for safeguarding large language models (LLMs) against queries with harmful intents. However, the underlying working mechanisms of safety prompts have not been unraveled yet, restricting the possibility of automatically optimizing them to improve LLM safet...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	425,400
2306.07678	Localization of Just Noticeable Difference for Image Compression	The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given reference image and a compression algorithm represents the minimal level of compression that causes noticeable differences in the reconstruction...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	373,110
2304.00334	TalkCLIP: Talking Head Generation with Text-Guided Expressive Speaking Styles	Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to provide expression information, which may be difficult to find and hence limits their usage. In this work, we propose TalkCLIP, a framework...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,638
2403.11307	An upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem	As an important part of genetic algorithms (GAs), mutation operators is widely used in evolutionary algorithms to solve $\mathcal{NP}$-hard problems because it can increase the population diversity of individual. Due to limitations in mathematical tools, the mutation probability of the mutation operator is primarily em...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	438,633
1604.06785	Rank-Deficient Solutions for Optimal Signaling over Wiretap MIMO Channels	Capacity-achieving signaling strategies for the Gaussian wiretap MIMO channel are investigated without the degradedness assumption. In addition to known solutions, a number of new rank-deficient solutions for the optimal transmit covariance matrix are obtained. The case of a weak eavesdropper is considered in detail an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,993
2411.13682	Differentially Private Learning Beyond the Classical Dimensionality Regime	We initiate the study of differentially private learning in the proportional dimensionality regime, in which the number of data samples $n$ and problem dimension $d$ approach infinity at rates proportional to one another, meaning that $d/n\to\delta$ as $n\to\infty$ for an arbitrary, given constant $\delta\in(0,\infty)$...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	509,880
2402.09430	WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing	WiFi-based human sensing has exhibited remarkable potential to analyze user behaviors in a non-intrusive and device-free manner, benefiting applications as diverse as smart homes and healthcare. However, most previous works focus on single-user sensing, which has limited practicability in scenarios involving multiple u...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	429,513
2412.09401	SLAM3R: Real-Time Dense Scene Reconstruction from Monocular RGB Videos	In this paper, we introduce SLAM3R, a novel and effective monocular RGB SLAM system for real-time and high-quality dense 3D reconstruction. SLAM3R provides an end-to-end solution by seamlessly integrating local 3D reconstruction and global coordinate registration through feed-forward neural networks. Given an input vid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,466
2411.13587	Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics	Recently in robotics, Vision-Language-Action (VLA) models have emerged as a transformative approach, enabling robots to execute complex tasks by integrating visual and linguistic inputs within an end-to-end learning framework. While VLA models offer significant capabilities, they also introduce new attack surfaces, mak...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	509,843
2106.07270	Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly	Despite their contributions to the financial efficiency and environmental sustainability of industrial processes, robotic assembly and disassembly have been understudied in the existing literature. This is in contradiction to their importance in realizing the Fourth Industrial Revolution. More specifically, although mo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	240,850
2109.03495	Temporal RoI Align for Video Object Recognition	Video object detection is challenging in the presence of appearance deterioration in certain video frames. Therefore, it is a natural choice to aggregate temporal information from other frames of the same video into the current frame. However, RoI Align, as one of the most core procedures of video detectors, still rema...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	254,092
0901.2684	Distributed Large Scale Network Utility Maximization	Recent work by Zymnis et al. proposes an efficient primal-dual interior-point method, using a truncated Newton method, for solving the network utility maximization (NUM) problem. This method has shown superior performance relative to the traditional dual-decomposition approach. Other recent work by Bickson et al. shows...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,999
2306.06595	Neural Projection Mapping Using Reflectance Fields	We introduce a high resolution spatially adaptive light source, or a projector, into a neural reflectance field that allows to both calibrate the projector and photo realistic light editing. The projected texture is fully differentiable with respect to all scene parameters, and can be optimized to yield a desired appea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	372,674
2007.05080	A Benchmark for Inpainting of Clothing Images with Irregular Holes	Fashion image understanding is an active research field with a large number of practical applications for the industry. Despite its practical impacts on intelligent fashion analysis systems, clothing image inpainting has not been extensively examined yet. For that matter, we present an extensive benchmark of clothing i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,557
2208.10895	A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey	Deep neural network based object detectors are continuously evolving and are used in a multitude of applications, each having its own set of requirements. While safety-critical applications need high accuracy and reliability, low-latency tasks need resource and energy-efficient networks. Real-time detectors, which are ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	314,240
2012.15386	Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions	Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers. State-of-the-art adversarial example detection methods characterize an input example as adversarial either by quantifying the magnitude of feature variations under multiple perturbations or by measuring its di...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	213,763
2307.09104	Division Gets Better: Learning Brightness-Aware and Detail-Sensitive Representations for Low-Light Image Enhancement	Low-light image enhancement strives to improve the contrast, adjust the visibility, and restore the distortion in color and texture. Existing methods usually pay more attention to improving the visibility and contrast via increasing the lightness of low-light images, while disregarding the significance of color and tex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,058
2402.15089	AttributionBench: How Hard is Automatic Attribution Evaluation?	Modern generative search engines enhance the reliability of large language model (LLM) responses by providing cited evidence. However, evaluating the answer's attribution, i.e., whether every claim within the generated responses is fully supported by its cited evidence, remains an open problem. This verification, tradi...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	431,985
1904.07021	Fatigue design load calculations of the offshore NREL 5MW benchmark turbine using quadrature rule techniques	A novel approach is proposed to reduce, compared to the conventional binning approach, the large number of aeroelastic code evaluations that are necessary to obtain equivalent loads acting on wind turbines. These loads describe the effect of long-term environmental variability on the fatigue loads of a horizontal-axis ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	127,690
1101.3354	Introduction to the Bag of Features Paradigm for Image Classification and Retrieval	The past decade has seen the growing popularity of Bag of Features (BoF) approaches to many computer vision tasks, including image classification, video search, robot localization, and texture recognition. Part of the appeal is simplicity. BoF methods are based on orderless collections of quantized local image descript...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	8,842
2109.12426	Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search	Neural architecture search automates neural network design and has achieved state-of-the-art results in many deep learning applications. While recent literature has focused on designing networks to maximize accuracy, little work has been conducted to understand the compatibility of architecture design spaces to varying...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	257,284
2412.11152	Dual-Schedule Inversion: Training- and Tuning-Free Inversion for Real Image Editing	Text-conditional image editing is a practical AIGC task that has recently emerged with great commercial and academic value. For real image editing, most diffusion model-based methods use DDIM Inversion as the first stage before editing. However, DDIM Inversion often results in reconstruction failure, leading to unsatis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,280

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