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
2308.01270	BCDDO: Binary Child Drawing Development Optimization	A lately created metaheuristic algorithm called Child Drawing Development Optimization (CDDO) has proven to be effective in a number of benchmark tests. A Binary Child Drawing Development Optimization (BCDDO) is suggested for choosing the wrapper features in this study. To achieve the best classification accuracy, a su...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	383,205
2502.02904	ScholaWrite: A Dataset of End-to-End Scholarly Writing Process	Writing is a cognitively demanding task involving continuous decision-making, heavy use of working memory, and frequent switching between multiple activities. Scholarly writing is particularly complex as it requires authors to coordinate many pieces of multiform knowledge. To fully understand writers' cognitive thought...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	530,518
2009.08276	Video based real-time positional tracker	We propose a system that uses video as the input to track the position of objects relative to their surrounding environment in real-time. The neural network employed is trained on a 100% synthetic dataset coming from our own automated generator. The positional tracker relies on a range of 1 to n video cameras placed ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,189
2210.16797	Adaptive and Fair Deployment Approach to Balance Offload Traffic in Multi-UAV Cellular Networks	Unmanned aerial vehicle-aided communication (UAB-BS) is a promising solution to establish rapid wireless connectivity in sudden/temporary crowded events because of its more flexibility and mobility features than conventional ground base station (GBS). Because of these benefits, UAV-BSs can easily be deployed at high al...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	327,461
2406.16938	Unmixing Noise from Hawkes Process to Model Learned Physiological Events	Physiological signal analysis often involves identifying events crucial to understanding biological dynamics. Traditional methods rely on handcrafted procedures or supervised learning, presenting challenges such as expert dependence, lack of robustness, and the need for extensive labeled data. Data-driven methods like ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	467,353
1803.08995	Iterative Low-Rank Approximation for CNN Compression	Deep convolutional neural networks contain tens of millions of parameters, making them impossible to work efficiently on embedded devices. We propose iterative approach of applying low-rank approximation to compress deep convolutional neural networks. Since classification and object detection are the most favored tasks...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,389
2111.15199	Semi-Supervised 3D Hand Shape and Pose Estimation with Label Propagation	To obtain 3D annotations, we are restricted to controlled environments or synthetic datasets, leading us to 3D datasets with less generalizability to real-world scenarios. To tackle this issue in the context of semi-supervised 3D hand shape and pose estimation, we propose the Pose Alignment network to propagate 3D anno...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,857
1911.08891	Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement	Identifying new user intents is an essential task in the dialogue system. However, it is hard to get satisfying clustering results since the definition of intents is strongly guided by prior knowledge. Existing methods incorporate prior knowledge by intensive feature engineering, which not only leads to overfitting but...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	154,342
2201.10577	Shared Cache Coded Caching Schemes with known User-to-Cache Association Profile using Placement Delivery Arrays	This work considers the coded caching problem with shared caches, where users share the caches, and each user gets access only to one cache. The user-to-cache association is assumed to be known at the server during the placement phase. We focus on the schemes derived using placement delivery arrays (PDAs). The PDAs wer...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	277,034
1703.06630	Automatic Text Summarization Approaches to Speed up Topic Model Learning Process	The number of documents available into Internet moves each day up. For this reason, processing this amount of information effectively and expressibly becomes a major concern for companies and scientists. Methods that represent a textual document by a topic representation are widely used in Information Retrieval (IR) to...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	70,259
1906.03951	SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models	Remarkable achievements have been attained by deep neural networks in various applications. However, the increasing depth and width of such models also lead to explosive growth in both storage and computation, which has restricted the deployment of deep neural networks on resource-limited edge devices. To address this ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	134,547
2205.04613	Calibrating for Class Weights by Modeling Machine Learning	A much studied issue is the extent to which the confidence scores provided by machine learning algorithms are calibrated to ground truth probabilities. Our starting point is that calibration is seemingly incompatible with class weighting, a technique often employed when one class is less common (class imbalance) or wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	295,690
2410.09864	AuthFace: Towards Authentic Blind Face Restoration with Face-oriented Generative Diffusion Prior	Blind face restoration (BFR) is a fundamental and challenging problem in computer vision. To faithfully restore high-quality (HQ) photos from poor-quality ones, recent research endeavors predominantly rely on facial image priors from the powerful pretrained text-to-image (T2I) diffusion models. However, such priors oft...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	497,800
2410.09186	Learning Algorithms Made Simple	In this paper, we discuss learning algorithms and their importance in different types of applications which includes training to identify important patterns and features in a straightforward, easy-to-understand manner. We will review the main concepts of artificial intelligence (AI), machine learning (ML), deep learnin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	497,473
2109.08666	Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields	This paper presents a convex-analytic framework to learn sparse graphs from data. While our problem formulation is inspired by an extension of the graphical lasso using the so-called combinatorial graph Laplacian framework, a key difference is the use of a nonconvex alternative to the $\ell_1$ norm to attain graphs wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,972
2105.03943	gComm: An environment for investigating generalization in Grounded Language Acquisition	gComm is a step towards developing a robust platform to foster research in grounded language acquisition in a more challenging and realistic setting. It comprises a 2-d grid environment with a set of agents (a stationary speaker and a mobile listener connected via a communication channel) exposed to a continuous array ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	234,330
1607.08584	Connectionist Temporal Modeling for Weakly Supervised Action Labeling	We propose a weakly-supervised framework for action labeling in video, where only the order of occurring actions is required during training time. The key challenge is that the per-frame alignments between the input (video) and label (action) sequences are unknown during training. We address this by introducing the Ext...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,175
1704.03493	Creativity: Generating Diverse Questions using Variational Autoencoders	Generating diverse questions for given images is an important task for computational education, entertainment and AI assistants. Different from many conventional prediction techniques is the need for algorithms to generate a diverse set of plausible questions, which we refer to as "creativity". In this paper we propose...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,637
1212.1296	Distributed Model Predictive Consensus via the Alternating Direction Method of Multipliers	We propose a distributed optimization method for solving a distributed model predictive consensus problem. The goal is to design a distributed controller for a network of dynamical systems to optimize a coupled objective function while respecting state and input constraints. The distributed optimization method is an au...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	20,163
2407.07821	When to Accept Automated Predictions and When to Defer to Human Judgment?	Ensuring the reliability and safety of automated decision-making is crucial. It is well-known that data distribution shifts in machine learning can produce unreliable outcomes. This paper proposes a new approach for measuring the reliability of predictions under distribution shifts. We analyze how the outputs of a trai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	471,916
1507.00280	Network Lasso: Clustering and Optimization in Large Graphs	Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. T...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	44,741
1504.03033	On the stability of the PWP method	The PWP method was introduced by Diaz in 2009 as a technique for measuring indirect influences in complex networks. It depends on a matrix D, provided by the user, called the matrix of direct influences, and on a positive real parameter which is part of the method itself. We study changes in the method's predictions as...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	41,989
2012.14323	Freshness-Optimal Caching for Information Updating Systems with Limited Cache Storage Capacity	In this paper, we investigate a cache updating system with a server containing $N$ files, $K$ relays and $M$ users. The server keeps the freshest versions of the files which are updated with fixed rates. Each relay can download the fresh files from the server in a certain period of time. Each user can get the fresh fil...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	213,475
2304.06447	PDFVQA: A New Dataset for Real-World VQA on PDF Documents	Document-based Visual Question Answering examines the document understanding of document images in conditions of natural language questions. We proposed a new document-based VQA dataset, PDF-VQA, to comprehensively examine the document understanding from various aspects, including document element recognition, document...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	357,978
2204.07613	Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation	Automated segmentation of retinal optical coherence tomography (OCT) images has become an important recent direction in machine learning for medical applications. We hypothesize that the anatomic structure of layers and their high-frequency variation in OCT images make retinal OCT a fitting choice for extracting spectr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	291,766
2104.08340	An Analysis of a BERT Deep Learning Strategy on a Technology Assisted Review Task	Document screening is a central task within Evidenced Based Medicine, which is a clinical discipline that supplements scientific proof to back medical decisions. Given the recent advances in DL (Deep Learning) methods applied to Information Retrieval tasks, I propose a DL document classification approach with BERT or P...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	230,756
1809.00386	A Study of Dynamic Multipath Clusters at 60 GHz in a Large Indoor Environment	The available geometry-based stochastic channel models (GSCMs) at millimetre-wave (mmWave) frequencies do not necessarily retain spatial consistency for simulated channels, which is essential for small cells with ultra-dense users. In this paper, we work on cluster parameterization for the COST 2100 channel model using...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	106,568
1209.4683	Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds	In a wireless system with a large number of distributed nodes, the quality of communication can be greatly improved by pooling the nodes to perform joint transmission/reception. In this paper, we consider the problem of optimally selecting a subset of nodes from potentially a large number of candidates to form a virtua...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,665
2402.07963	SPO: Sequential Monte Carlo Policy Optimisation	Leveraging planning during learning and decision-making is central to the long-term development of intelligent agents. Recent works have successfully combined tree-based search methods and self-play learning mechanisms to this end. However, these methods typically face scaling challenges due to the sequential nature of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,917
1907.00854	Katecheo: A Portable and Modular System for Multi-Topic Question Answering	We introduce a modular system that can be deployed on any Kubernetes cluster for question answering via REST API. This system, called Katecheo, includes three configurable modules that collectively enable identification of questions, classification of those questions into topics, document search, and reading comprehens...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	137,159
2407.10657	An Empirical Study of Validating Synthetic Data for Formula Generation	Large language models (LLMs) can be leveraged to help with writing formulas in spreadsheets, but resources on these formulas are scarce, impacting both the base performance of pre-trained models and limiting the ability to fine-tune them. Given a corpus of formulas, we can use a(nother) model to generate synthetic natu...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	473,068
1112.6275	Reasoning About Strategies: On the Model-Checking Problem	In open systems verification, to formally check for reliability, one needs an appropriate formalism to model the interaction between agents and express the correctness of the system no matter how the environment behaves. An important contribution in this context is given by modal logics for strategic ability, in the se...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	13,613
1506.07866	Camera Calibration from Dynamic Silhouettes Using Motion Barcodes	Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use information from dynamic objects in the scene for suggesting point and line correspondences. We propose a speed up of about two orders of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,560
2203.17067	CADG: A Model Based on Cross Attention for Domain Generalization	In Domain Generalization (DG) tasks, models are trained by using only training data from the source domains to achieve generalization on an unseen target domain, this will suffer from the distribution shift problem. So it's important to learn a classifier to focus on the common representation which can be used to class...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,029
2304.02328	Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck	This paper studies the multimodal named entity recognition (MNER) and multimodal relation extraction (MRE), which are important for multimedia social platform analysis. The core of MNER and MRE lies in incorporating evident visual information to enhance textual semantics, where two issues inherently demand investigatio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	356,404
2411.00372	Generalizability of Memorization Neural Networks	The neural network memorization problem is to study the expressive power of neural networks to interpolate a finite dataset. Although memorization is widely believed to have a close relationship with the strong generalizability of deep learning when using over-parameterized models, to the best of our knowledge, there e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	504,563
1903.04407	Accuracy Booster: Performance Boosting using Feature Map Re-calibration	Convolution Neural Networks (CNN) have been extremely successful in solving intensive computer vision tasks. The convolutional filters used in CNNs have played a major role in this success, by extracting useful features from the inputs. Recently researchers have tried to boost the performance of CNNs by re-calibrating ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	123,967
2309.04888	Semi-supervised Instance Segmentation with a Learned Shape Prior	To date, most instance segmentation approaches are based on supervised learning that requires a considerable amount of annotated object contours as training ground truth. Here, we propose a framework that searches for the target object based on a shape prior. The shape prior model is learned with a variational autoenco...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,889
2110.12987	Optimization-Based GenQSGD for Federated Edge Learning	Optimal algorithm design for federated learning (FL) remains an open problem. This paper explores the full potential of FL in practical edge computing systems where workers may have different computation and communication capabilities, and quantized intermediate model updates are sent between the server and workers. Fi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,037
2204.04492	S4OD: Semi-Supervised learning for Single-Stage Object Detection	Single-stage detectors suffer from extreme foreground-background class imbalance, while two-stage detectors do not. Therefore, in semi-supervised object detection, two-stage detectors can deliver remarkable performance by only selecting high-quality pseudo labels based on classification scores. However, directly applyi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,674
2309.10360	OccluTrack: Rethinking Awareness of Occlusion for Enhancing Multiple Pedestrian Tracking	Multiple pedestrian tracking faces the challenge of tracking pedestrians in the presence of occlusion. Existing methods suffer from inaccurate motion estimation, appearance feature extraction, and association due to occlusion, leading to inadequate Identification F1-Score (IDF1), excessive ID switches (IDSw), and insuf...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	392,978
2408.08684	Research on Personalized Compression Algorithm for Pre-trained Models Based on Homomorphic Entropy Increase	In this article, we explore the challenges and evolution of two key technologies in the current field of AI: Vision Transformer model and Large Language Model (LLM). Vision Transformer captures global information by splitting images into small pieces and leveraging Transformer's multi-head attention mechanism, but its ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	481,105
2210.07415	Noise Audits Improve Moral Foundation Classification	Morality plays an important role in culture, identity, and emotion. Recent advances in natural language processing have shown that it is possible to classify moral values expressed in text at scale. Morality classification relies on human annotators to label the moral expressions in text, which provides training data t...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	323,693
2402.05860	Privacy-Preserving Synthetic Continual Semantic Segmentation for Robotic Surgery	Deep Neural Networks (DNNs) based semantic segmentation of the robotic instruments and tissues can enhance the precision of surgical activities in robot-assisted surgery. However, in biological learning, DNNs cannot learn incremental tasks over time and exhibit catastrophic forgetting, which refers to the sharp decline...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	428,032
2202.00783	Modeling ventilation in a low-income house in Dhaka, Bangladesh	According to UNICEF, pneumonia is the leading cause of death in children under 5. 70% of worldwide pneumonia deaths occur in only 15 countries, including Bangladesh. Previous research has indicated a potential association between the incidence of pneumonia and the presence of cross-ventilation in slum housing in Dhaka,...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	278,254
2309.03734	ClusterFusion: Leveraging Radar Spatial Features for Radar-Camera 3D Object Detection in Autonomous Vehicles	Thanks to the complementary nature of millimeter wave radar and camera, deep learning-based radar-camera 3D object detection methods may reliably produce accurate detections even in low-visibility conditions. This makes them preferable to use in autonomous vehicles' perception systems, especially as the combined cost o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,488
1912.10703	Variational Recurrent Models for Solving Partially Observable Control Tasks	In partially observable (PO) environments, deep reinforcement learning (RL) agents often suffer from unsatisfactory performance, since two problems need to be tackled together: how to extract information from the raw observations to solve the task, and how to improve the policy. In this study, we propose an RL algorith...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	158,385
2309.01201	Distributed robust optimization for multi-agent systems with guaranteed finite-time convergence	A novel distributed algorithm is proposed for finite-time converging to a feasible consensus solution satisfying global optimality to a certain accuracy of the distributed robust convex optimization problem (DRCO) subject to bounded uncertainty under a uniformly strongly connected network. Firstly, a distributed lower ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	389,590
2007.01790	Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning	Wireless connectivity is instrumental in enabling scalable federated learning (FL), yet wireless channels bring challenges for model training, in which channel randomness perturbs each worker's model update while multiple workers' updates incur significant interference under limited bandwidth. To address these challeng...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	185,534
2101.07365	Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation	We propose a privacy-preserving Naive Bayes classifier and apply it to the problem of private text classification. In this setting, a party (Alice) holds a text message, while another party (Bob) holds a classifier. At the end of the protocol, Alice will only learn the result of the classifier applied to her text input...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	216,007
2002.01169	Graph Representation Learning via Graphical Mutual Information Maximization	The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expressive representations without external supervision. This paper investigates how to preserve and extract the abundant information from graph-s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	162,590
2408.05336	Logically Constrained Robotics Transformers for Enhanced Perception-Action Planning	With the advent of large foundation model based planning, there is a dire need to ensure their output aligns with the stakeholder's intent. When these models are deployed in the real world, the need for alignment is magnified due to the potential cost to life and infrastructure due to unexpected faliures. Temporal Logi...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	479,734
2209.11113	Decentralized Distributed Expert Assisted Learning (D2EAL) approach for cooperative target-tracking	This paper addresses the problem of cooperative target tracking using a heterogeneous multi-robot system, where the robots are communicating over a dynamic communication network, and heterogeneity is in terms of different types of sensors and prediction algorithms installed in the robots. The problem is cast into a dis...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	319,080
2410.00933	StreamEnsemble: Predictive Queries over Spatiotemporal Streaming Data	Predictive queries over spatiotemporal (ST) stream data pose significant data processing and analysis challenges. ST data streams involve a set of time series whose data distributions may vary in space and time, exhibiting multiple distinct patterns. In this context, assuming a single machine learning model would adequ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	493,541
2210.00726	Statistical Efficiency of Score Matching: The View from Isoperimetry	Deep generative models parametrized up to a normalizing constant (e.g. energy-based models) are difficult to train by maximizing the likelihood of the data because the likelihood and/or gradients thereof cannot be explicitly or efficiently written down. Score matching is a training method, whereby instead of fitting th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	320,979
1609.07183	An extended characterization of a class of optimal three-weight cyclic codes over any finite field	A characterization of a class of optimal three-weight cyclic codes of dimension 3 over any finite field was recently presented in [10]. Shortly after this, a generalization for the sufficient numerical conditions of such characterization was given in [3]. The main purpose of this work is to show that the numerical cond...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	61,401
2306.01504	Syst\`eme de recommandations bas\'e sur les contraintes pour les simulations de gestion de crise	In the context of the evacuation of populations, some citizens/volunteers may want and be able to participate in the evacuation of populations in difficulty by coming to lend a hand to emergency/evacuation vehicles with their own vehicles. One way of framing these impulses of solidarity would be to be able to list in r...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	370,487
2007.04928	Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer	Fast motion feedback is crucial in computer-aided surgery (CAS) on moving tissue. Image-assistance in safety-critical vision applications requires a dense tracking of tissue motion. This can be done using optical flow (OF). Accurate motion predictions at high processing rates lead to higher patient safety. Current deep...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,513
1901.09786	AlteregoNets: a way to human augmentation	A person dependent network, called an AlterEgo net, is proposed for development. The networks are created per person. It receives at input an object descriptions and outputs a simulation of the internal person's representation of the objects. The network generates a textual stream resembling the narrative stream of con...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	119,837
2007.15131	Learning To Pay Attention To Mistakes	In convolutional neural network based medical image segmentation, the periphery of foreground regions representing malignant tissues may be disproportionately assigned as belonging to the background class of healthy tissues \cite{attenUnet}\cite{AttenUnet2018}\cite{InterSeg}\cite{UnetFrontNeuro}\cite{LearnActiveContour...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	189,576
2401.10556	Symbol as Points: Panoptic Symbol Spotting via Point-based Representation	This work studies the problem of panoptic symbol spotting, which is to spot and parse both countable object instances (windows, doors, tables, etc.) and uncountable stuff (wall, railing, etc.) from computer-aided design (CAD) drawings. Existing methods typically involve either rasterizing the vector graphics into image...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	422,688
2502.13652	C2T: A Classifier-Based Tree Construction Method in Speculative Decoding	The growing scale of Large Language Models (LLMs) has exacerbated inference latency and computational costs. Speculative decoding methods, which aim to mitigate these issues, often face inefficiencies in the construction of token trees and the verification of candidate tokens. Existing strategies, including chain mode,...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	535,456
2407.02607	Product Geometries on Cholesky Manifolds with Applications to SPD Manifolds	This paper presents two new metrics on the Symmetric Positive Definite (SPD) manifold via the Cholesky manifold, i.e., the space of lower triangular matrices with positive diagonal elements. We first unveil that the existing popular Riemannian metric on the Cholesky manifold can be generally characterized as the produc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	469,803
2501.18781	A consistent diffuse-interface finite element approach to rapid melt--vapor dynamics in metal additive manufacturing	Metal additive manufacturing via laser-based powder bed fusion (PBF-LB/M) faces performance-critical challenges due to complex melt pool and vapor dynamics, often oversimplified by computational models that neglect crucial aspects, such as vapor jet formation. To address this limitation, we propose a consistent computa...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	528,849
2303.06442	Fine-grained Visual Classification with High-temperature Refinement and Background Suppression	Fine-grained visual classification is a challenging task due to the high similarity between categories and distinct differences among data within one single category. To address the challenges, previous strategies have focused on localizing subtle discrepancies between categories and enhencing the discriminative featur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,850
2303.07881	An Algorithm to find the Generators of Multidimensional Cyclic Codes over a Finite Chain Ring	The aim of this paper is to determine the algebraic structure of multidimensional cyclic codes over a finite chain ring $\mathfrak{R}$. An algorithm to find the generator polynomials of $n$ dimensional ($n$D) cyclic codes of length $m_{1}m_{2}\dots m_{n}$ over $\mathfrak{R}$ has been developed using the generator polyn...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	351,420
2312.07466	Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery	Besides performance, efficiency is a key design driver of technologies supporting vehicular perception. Indeed, a well-balanced trade-off between performance and energy consumption is crucial for the sustainability of autonomous vehicles. In this context, the diversity of real-world contexts in which autonomous vehicle...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	414,932
1911.05701	Transfer Value Iteration Networks	Value iteration networks (VINs) have been demonstrated to have a good generalization ability for reinforcement learning tasks across similar domains. However, based on our experiments, a policy learned by VINs still fail to generalize well on the domain whose action space and feature space are not identical to those in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	153,344
2211.15663	Hand-Object Interaction Image Generation	In this work, we are dedicated to a new task, i.e., hand-object interaction image generation, which aims to conditionally generate the hand-object image under the given hand, object and their interaction status. This task is challenging and research-worthy in many potential application scenarios, such as AR/VR games an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,354
2205.04052	Robot formation control in nonlinear manifold using Koopman operator theory	Formation control of multi-agent systems has been a prominent research topic, spanning both theoretical and practical domains over the past two decades. Our study delves into the leader-follower framework, addressing two critical, previously overlooked aspects. Firstly, we investigate the impact of an unknown nonlinear...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	295,519
2402.13771	Mask-up: Investigating Biases in Face Re-identification for Masked Faces	AI based Face Recognition Systems (FRSs) are now widely distributed and deployed as MLaaS solutions all over the world, moreso since the COVID-19 pandemic for tasks ranging from validating individuals' faces while buying SIM cards to surveillance of citizens. Extensive biases have been reported against marginalized gro...	true	false	false	false	true	false	false	false	false	false	false	true	false	true	false	false	false	false	431,404
1910.13580	Domain Generalization via Model-Agnostic Learning of Semantic Features	Generalization capability to unseen domains is crucial for machine learning models when deploying to real-world conditions. We investigate the challenging problem of domain generalization, i.e., training a model on multi-domain source data such that it can directly generalize to target domains with unknown statistics. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	151,425
2211.15407	Fine-tuned Sentiment Analysis of COVID-19 Vaccine-Related Social Media Data: Comparative Study	This study investigated and compared public sentiment related to COVID-19 vaccines expressed on two popular social media platforms, Reddit and Twitter, harvested from January 1, 2020, to March 1, 2022. To accomplish this task, we created a fine-tuned DistilRoBERTa model to predict sentiments of approximately 9.5 millio...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	333,246
2011.10428	Topic modelling discourse dynamics in historical newspapers	This paper addresses methodological issues in diachronic data analysis for historical research. We apply two families of topic models (LDA and DTM) on a relatively large set of historical newspapers, with the aim of capturing and understanding discourse dynamics. Our case study focuses on newspapers and periodicals pub...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	207,506
2009.03092	KoSpeech: Open-Source Toolkit for End-to-End Korean Speech Recognition	We present KoSpeech, an open-source software, which is modular and extensible end-to-end Korean automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch. Several automatic speech recognition open-source toolkits have been released, but all of them deal with non-Korean languages, such as Eng...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	194,742
1703.09193	A Cost-based Optimizer for Gradient Descent Optimization	As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execut...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	70,714
2306.05283	A Method for Detecting Murmurous Heart Sounds based on Self-similar Properties	A heart murmur is an atypical sound produced by the flow of blood through the heart. It can be a sign of a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identifying murmurous heart sounds do not fully utilize the valuab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,126
2001.05443	Robotic Grasp Manipulation Using Evolutionary Computing and Deep Reinforcement Learning	Intelligent Object manipulation for grasping is a challenging problem for robots. Unlike robots, humans almost immediately know how to manipulate objects for grasping due to learning over the years. A grown woman can grasp objects more skilfully than a child because of learning skills developed over years, the absence ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	160,542
2107.07480	Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update	In second-order optimization, a potential bottleneck can be computing the Hessian matrix of the optimized function at every iteration. Randomized sketching has emerged as a powerful technique for constructing estimates of the Hessian which can be used to perform approximate Newton steps. This involves multiplication by...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	246,436
2405.07354	SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset	The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics. Specifically, extracting audio commentaries with ASR provides valuable insights into the events of the game, and opens the door to several downstream applications such as automatic highlight ge...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	453,680
2308.13198	Journey to the Center of the Knowledge Neurons: Discoveries of Language-Independent Knowledge Neurons and Degenerate Knowledge Neurons	Pre-trained language models (PLMs) contain vast amounts of factual knowledge, but how the knowledge is stored in the parameters remains unclear. This paper delves into the complex task of understanding how factual knowledge is stored in multilingual PLMs, and introduces the Architecture-adapted Multilingual Integrated ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	387,821
2305.08388	A lower bound on the field size of convolutional codes with a maximum distance profile and an improved construction	Convolutional codes with a maximum distance profile attain the largest possible column distances for the maximum number of time instants and thus have outstanding error-correcting capability especially for streaming applications. Explicit constructions of such codes are scarce in the literature. In particular, known co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	364,269
2305.18222	survAIval: Survival Analysis with the Eyes of AI	In this study, we propose a novel approach to enrich the training data for automated driving by using a self-designed driving simulator and two human drivers to generate safety-critical corner cases in a short period of time, as already presented in~\cite{kowol22simulator}. Our results show that incorporating these cor...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	368,904
2003.06129	LIBRE: The Multiple 3D LiDAR Dataset	In this work, we present LIBRE: LiDAR Benchmarking and Reference, a first-of-its-kind dataset featuring 10 different LiDAR sensors, covering a range of manufacturers, models, and laser configurations. Data captured independently from each sensor includes three different environments and configurations: static targets, ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	168,035
2312.04845	Data-Driven Identification of Attack-free Sensors in Networked Control Systems	This paper proposes a data-driven framework to identify the attack-free sensors in a networked control system when some of the sensors are corrupted by an adversary. An operator with access to offline input-output attack-free trajectories of the plant is considered. Then, a data-driven algorithm is proposed to identify...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	413,855
2203.03245	Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios	Human behavior forecasting during human-human interactions is of utmost importance to provide robotic or virtual agents with social intelligence. This problem is especially challenging for scenarios that are highly driven by interpersonal dynamics. In this work, we present the first systematic comparison of state-of-th...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	284,026
1104.0742	Accelerating Growth and Size-dependent Distribution of Human Activities Online	Research on human online activities usually assumes that total activity $T$ increases linearly with active population $P$, that is, $T\propto P^{\gamma}(\gamma=1)$. However, we find examples of systems where total activity grows faster than active population. Our study shows that the power law relationship $T\propto P^...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,868
2103.01302	Coarse-Fine Networks for Temporal Activity Detection in Videos	In this paper, we introduce Coarse-Fine Networks, a two-stream architecture which benefits from different abstractions of temporal resolution to learn better video representations for long-term motion. Traditional Video models process inputs at one (or few) fixed temporal resolution without any dynamic frame selection....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	222,572
2203.13800	Continuous Dynamic-NeRF: Spline-NeRF	The problem of reconstructing continuous functions over time is important for problems such as reconstructing moving scenes, and interpolating between time steps. Previous approaches that use deep-learning rely on regularization to ensure that reconstructions are approximately continuous, which works well on short sequ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,762
2307.00268	Hiding in Plain Sight: Differential Privacy Noise Exploitation for Evasion-resilient Localized Poisoning Attacks in Multiagent Reinforcement Learning	Lately, differential privacy (DP) has been introduced in cooperative multiagent reinforcement learning (CMARL) to safeguard the agents' privacy against adversarial inference during knowledge sharing. Nevertheless, we argue that the noise introduced by DP mechanisms may inadvertently give rise to a novel poisoning threa...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	true	false	false	false	376,939
2409.03658	A DNN Biophysics Model with Topological and Electrostatic Features	In this project, we provide a deep-learning neural network (DNN) based biophysics model to predict protein properties. The model uses multi-scale and uniform topological and electrostatic features generated with protein structural information and force field, which governs the molecular mechanics. The topological featu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,117
2011.10118	Batteries, camera, action! Learning a semantic control space for expressive robot cinematography	Aerial vehicles are revolutionizing the way film-makers can capture shots of actors by composing novel aerial and dynamic viewpoints. However, despite great advancements in autonomous flight technology, generating expressive camera behaviors is still a challenge and requires non-technical users to edit a large number o...	true	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	true	207,417
1705.05668	Transmitter Beam Selection in Millimeter-wave MIMO with In-Band Position-Aiding	Emerging wireless communication systems will be characterized by a tight coupling between communication and positioning. This is particularly apparent in millimeter-wave (mm-wave) communications, where devices use a large number of antennas and the propagation is well described by geometric channel models. For mm-wave ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	73,533
2409.16709	Pose-Guided Fine-Grained Sign Language Video Generation	Sign language videos are an important medium for spreading and learning sign language. However, most existing human image synthesis methods produce sign language images with details that are distorted, blurred, or structurally incorrect. They also produce sign language video frames with poor temporal consistency, with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,471
2010.11230	Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents	Turn-level user satisfaction is one of the most important performance metrics for conversational agents. It can be used to monitor the agent's performance and provide insights about defective user experiences. Moreover, a powerful satisfaction model can be used as an objective function that a conversational agent conti...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	202,163
2501.09753	SRE-Conv: Symmetric Rotation Equivariant Convolution for Biomedical Image Classification	Convolutional neural networks (CNNs) are essential tools for computer vision tasks, but they lack traditionally desired properties of extracted features that could further improve model performance, e.g., rotational equivariance. Such properties are ubiquitous in biomedical images, which often lack explicit orientation...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	525,257
1904.12413	A convolution recurrent autoencoder for spatio-temporal missing data imputation	When sensors collect spatio-temporal data in a large geographical area, the existence of missing data cannot be escaped. Missing data negatively impacts the performance of data analysis and machine learning algorithms. In this paper, we study deep autoencoders for missing data imputation in spatio-temporal problems. We...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,110
2402.18390	Neuromorphic Event-Driven Semantic Communication in Microgrids	Synergies between advanced communications, computing and artificial intelligence are unraveling new directions of coordinated operation and resiliency in microgrids. On one hand, coordination among sources is facilitated by distributed, privacy-minded processing at multiple locations, whereas on the other hand, it also...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	false	true	433,413
2005.02662	Consistent identification of continuous-time systems under multisine input signal excitation	For many years, the Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC) has been widely used for identification. The intersample behaviour of the input plays an important role in this method, and it has been shown recently that the SRIVC estimator is not consistent if an incorrect assump...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	175,946
2410.05710	PixLens: A Novel Framework for Disentangled Evaluation in Diffusion-Based Image Editing with Object Detection + SAM	Evaluating diffusion-based image-editing models is a crucial task in the field of Generative AI. Specifically, it is imperative to assess their capacity to execute diverse editing tasks while preserving the image content and realism. While recent developments in generative models have opened up previously unheard-of po...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	495,872

Subsets and Splits

No community queries yet

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