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
2209.02617	Priority Based Synchronization for Faster Learning in Games	Learning in games has been widely used to solve many cooperative multi-agent problems such as coverage control, consensus, self-reconfiguration or vehicle-target assignment. One standard approach in this domain is to formulate the problem as a potential game and to use an algorithm such as log-linear learning to achiev...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	316,263
2302.09450	Robust and Versatile Bipedal Jumping Control through Reinforcement Learning	This work aims to push the limits of agility for bipedal robots by enabling a torque-controlled bipedal robot to perform robust and versatile dynamic jumps in the real world. We present a reinforcement learning framework for training a robot to accomplish a large variety of jumping tasks, such as jumping to different l...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	346,430
1709.03669	Capture Point Trajectories for Reduced Knee Bend using Step Time Optimization	Traditional force-controlled bipedal walking utilizes highly bent knees, resulting in high torques as well as inefficient, and unnatural motions. Even with advanced planning of center of mass height trajectories, significant amounts of knee-bend can be required due to arbitrarily chosen step timing. In this work, we pr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	80,505
2111.07929	High-Rate Convolutional Codes with CRC-Aided List Decoding for Short Blocklengths	Recently, rate-$1/\omega$ zero-terminated and tail-biting convolutional codes (ZTCCs and TBCCs) with cyclic-redundancy-check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short blocklengths. This paper designs CRCs for rate-$(\omega-1)/\omega$ CCs with short block...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	266,517
2501.13959	Assisting Mathematical Formalization with A Learning-based Premise Retriever	Premise selection is a crucial yet challenging step in mathematical formalization, especially for users with limited experience. Due to the lack of available formalization projects, existing approaches that leverage language models often suffer from data scarcity. In this work, we introduce an innovative method for tra...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	526,905
2212.00855	Reward Function Optimization of a Deep Reinforcement Learning Collision Avoidance System	The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport category aircraft. Limitations in the currently mandated TCAS led the Federal Aviation Administration ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	334,218
0806.3227	A Non-differential Distributed Space-Time Coding for Partially-Coherent Cooperative Communication	In a distributed space-time coding scheme, based on the relay channel model, the relay nodes co-operate to linearly process the transmitted signal from the source and forward them to the destination such that the signal at the destination appears as a space time block code. Recently, a code design criteria for achievin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,943
2405.06522	Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning	In recent years, heterogeneous graph neural networks (HGNNs) have achieved excellent performance in handling heterogeneous information networks (HINs). Curriculum learning is a machine learning strategy where training examples are presented to a model in a structured order, starting with easy examples and gradually inc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	453,318
1111.1094	On Three Challenges of Artificial Living Systems and Embodied Evolution	Creating autonomous, self-supporting, self-replicating, sustainable systems is a great challenge. To some extent, understanding life means not only being able to create it from scratch, but also improving, supporting, saving it, or even making it even more advanced. This can be thought of as a long-term goal of living ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	12,911
2006.13462	DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model	Strong passwords are fundamental to the security of password-based user authentication systems. In recent years, much effort has been made to evaluate password strength or to generate strong passwords. Unfortunately, the usability or memorability of the strong passwords has been largely neglected. In this paper, we aim...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	183,920
2207.00165	Secure Forward Aggregation for Vertical Federated Neural Networks	Vertical federated learning (VFL) is attracting much attention because it enables cross-silo data cooperation in a privacy-preserving manner. While most research works in VFL focus on linear and tree models, deep models (e.g., neural networks) are not well studied in VFL. In this paper, we focus on SplitNN, a well-know...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	305,662
2012.04812	Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction	Relation extraction (RE) aims to predict a relation between a subject and an object in a sentence, while knowledge graph link prediction (KGLP) aims to predict a set of objects, O, given a subject and a relation from a knowledge graph. These two problems are closely related as their respective objectives are intertwine...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	210,576
2310.19415	Text-to-3D with Classifier Score Distillation	Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. While the usage of classifier-free guidance is well acknowledged to be crucial for successful optimization, it is considered an auxiliary tric...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	403,984
2412.04174	Supertoroid fitting of objects with holes for robotic grasping and scene generation	One of the strategies to detect the pose and shape of unknown objects is their geometric modeling, consisting on fitting known geometric entities. Classical geometric modeling fits simple shapes such as spheres or cylinders, but often those don't cover the variety of shapes that can be encountered. For those situations...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	514,292
2111.05426	DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution	The rapidly growing size of deep neural network (DNN) models and datasets has given rise to a variety of distribution strategies such as data, tensor-model, pipeline parallelism, and hybrid combinations thereof. Each of these strategies offers its own trade-offs and exhibits optimal performance across different models ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	265,788
2409.12150	Decoding Style: Efficient Fine-Tuning of LLMs for Image-Guided Outfit Recommendation with Preference	Personalized outfit recommendation remains a complex challenge, demanding both fashion compatibility understanding and trend awareness. This paper presents a novel framework that harnesses the expressive power of large language models (LLMs) for this task, mitigating their "black box" and static nature through fine-tun...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	489,456
2403.06339	FOAA: Flattened Outer Arithmetic Attention For Multimodal Tumor Classification	Fusion of multimodal healthcare data holds great promise to provide a holistic view of a patient's health, taking advantage of the complementarity of different modalities while leveraging their correlation. This paper proposes a simple and effective approach, inspired by attention, to fuse discriminative features from ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,400
2209.14475	Intrinsic Dimensionality Estimation within Tight Localities: A Theoretical and Experimental Analysis	Accurate estimation of Intrinsic Dimensionality (ID) is of crucial importance in many data mining and machine learning tasks, including dimensionality reduction, outlier detection, similarity search and subspace clustering. However, since their convergence generally requires sample sizes (that is, neighborhood sizes) o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	320,261
2405.20715	Transforming Japan Real Estate	The Japanese real estate market, valued over 35 trillion USD, offers significant investment opportunities. Accurate rent and price forecasting could provide a substantial competitive edge. This paper explores using alternative data variables to predict real estate performance in 1100 Japanese municipalities. A comprehe...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	459,486
2306.04249	DEMIST: A deep-learning-based task-specific denoising approach for myocardial perfusion SPECT	There is an important need for methods to process myocardial perfusion imaging (MPI) SPECT images acquired at lower radiation dose and/or acquisition time such that the processed images improve observer performance on the clinical task of detecting perfusion defects. To address this need, we build upon concepts from mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	371,668
2301.11542	Feasibility and Transferability of Transfer Learning: A Mathematical Framework	Transfer learning is an emerging and popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. Despite its numerous empirical successes, theoretical analysis for transfer learning is limited. In this paper we build for the first time, to the best of our knowl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,187
2405.15313	Enhancing Text-to-Image Editing via Hybrid Mask-Informed Fusion	Recently, text-to-image (T2I) editing has been greatly pushed forward by applying diffusion models. Despite the visual promise of the generated images, inconsistencies with the expected textual prompt remain prevalent. This paper aims to systematically improve the text-guided image editing techniques based on diffusion...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	456,867
2305.00191	Optimization of AoII and QAoII in Multi-User Links	We consider a network with multiple sources and a base station that send time-sensitive information to remote clients. The Age of Incorrect Information (AoII) captures the freshness of the informative pieces of status update packets at the destinations. We derive the closed-form Whittle Index formulation for a push-bas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	361,245
2406.12600	Generalization bounds for mixing processes via delayed online-to-PAC conversions	We study the generalization error of statistical learning algorithms in a non-i.i.d. setting, where the training data is sampled from a stationary mixing process. We develop an analytic framework for this scenario based on a reduction to online learning with delayed feedback. In particular, we show that the existence o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	465,480
1911.06930	Inverse Reinforcement Learning with Missing Data	We consider the problem of recovering an expert's reward function with inverse reinforcement learning (IRL) when there are missing/incomplete state-action pairs or observations in the demonstrated trajectories. This issue of missing trajectory data or information occurs in many situations, e.g., GPS signals from vehicl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	153,659
2502.14180	On the logical skills of large language models: evaluations using arbitrarily complex first-order logic problems	We present a method of generating first-order logic statements whose complexity can be controlled along multiple dimensions. We use this method to automatically create several datasets consisting of questions asking for the truth or falsity of first-order logic statements in Zermelo-Fraenkel set theory. While the resol...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	535,701
2412.12185	Graph Similarity Computation via Interpretable Neural Node Alignment	\Graph similarity computation is an essential task in many real-world graph-related applications such as retrieving the similar drugs given a query chemical compound or finding the user's potential friends from the social network database. Graph Edit Distance (GED) and Maximum Common Subgraphs (MCS) are the two commonl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	517,776
1709.07857	Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping	Instrumenting and collecting annotated visual grasping datasets to train modern machine learning algorithms can be extremely time-consuming and expensive. An appealing alternative is to use off-the-shelf simulators to render synthetic data for which ground-truth annotations are generated automatically. Unfortunately, m...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	81,352
2308.12666	Geodesic Mode Connectivity	Mode connectivity is a phenomenon where trained models are connected by a path of low loss. We reframe this in the context of Information Geometry, where neural networks are studied as spaces of parameterized distributions with curved geometry. We hypothesize that shortest paths in these spaces, known as geodesics, cor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	387,631
1909.09858	Versatile Compressive mmWave Hybrid Beamformer Codebook Design Framework	Hybrid beamforming (HB) architectures are attractive for wireless communication systems with large antenna arrays because the analog beamforming stage can significantly reduce the number of RF transceivers and hence power consumption. In HB systems, channel estimation (CE) becomes challenging due to indirect access by ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	146,376
1905.08412	Position Paper: From Multi-Agent Pathfinding to Pipe Routing	The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision-free paths for a number of agents, from a set of start locations to a set of goal positions in a known 2D environment. MAPF has been studied in theoretical computer science, robotics, and artificial intelligence over several decades, due to its im...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	131,463
2302.00119	Machine Translation Impact in E-commerce Multilingual Search	Previous work suggests that performance of cross-lingual information retrieval correlates highly with the quality of Machine Translation. However, there may be a threshold beyond which improving query translation quality yields little or no benefit to further improve the retrieval performance. This threshold may depend...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	343,105
2404.18628	Self-Avatar Animation in Virtual Reality: Impact of Motion Signals Artifacts on the Full-Body Pose Reconstruction	Virtual Reality (VR) applications have revolutionized user experiences by immersing individuals in interactive 3D environments. These environments find applications in numerous fields, including healthcare, education, or architecture. A significant aspect of VR is the inclusion of self-avatars, representing users withi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,335
1003.1399	Automatic derivation of domain terms and concept location based on the analysis of the identifiers	Developers express the meaning of the domain ideas in specifically selected identifiers and comments that form the target implemented code. Software maintenance requires knowledge and understanding of the encoded ideas. This paper presents a way how to create automatically domain vocabulary. Knowledge of domain vocabul...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	5,858
2210.01235	CaiRL: A High-Performance Reinforcement Learning Environment Toolkit	This paper addresses the dire need for a platform that efficiently provides a framework for running reinforcement learning (RL) experiments. We propose the CaiRL Environment Toolkit as an efficient, compatible, and more sustainable alternative for training learning agents and propose methods to develop more efficient e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	321,172
1901.08513	Finite-Time Stability of Switched and Hybrid Systems with Unstable Modes	In this work, we study finite-time stability of switched and hybrid systems in the presence of unstable modes. We present sufficient conditions in terms of multiple Lyapunov functions for the origin of the system to be finite time stable. More specifically, we show that even if the value of the Lyapunov function increa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	119,494
2112.05825	Revisiting Consistency Regularization for Semi-Supervised Learning	Consistency regularization is one of the most widely-used techniques for semi-supervised learning (SSL). Generally, the aim is to train a model that is invariant to various data augmentations. In this paper, we revisit this idea and find that enforcing invariance by decreasing distances between features from differentl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,965
1506.00893	SkILL - a Stochastic Inductive Logic Learner	Probabilistic Inductive Logic Programming (PILP) is a rel- atively unexplored area of Statistical Relational Learning which extends classic Inductive Logic Programming (ILP). This work introduces SkILL, a Stochastic Inductive Logic Learner, which takes probabilistic annotated data and produces First Order Logic theorie...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	43,727
2106.02105	A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks	Adversarial examples for neural network image classifiers are known to be transferable: examples optimized to be misclassified by a source classifier are often misclassified as well by classifiers with different architectures. However, targeted adversarial examples -- optimized to be classified as a chosen target class...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	238,724
1703.10580	MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction	In this work we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human face from a single in-the-wild color image. To this end, we combine a convolutional encoder network with an expert-designed generative model that serves as decoder. The c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,937
2407.10995	LionGuard: Building a Contextualized Moderation Classifier to Tackle Localized Unsafe Content	As large language models (LLMs) become increasingly prevalent in a wide variety of applications, concerns about the safety of their outputs have become more significant. Most efforts at safety-tuning or moderation today take on a predominantly Western-centric view of safety, especially for toxic, hateful, or violent sp...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	473,222
1901.01375	Analysis of a Two-Layer Neural Network via Displacement Convexity	Fitting a function by using linear combinations of a large number $N$ of `simple' components is one of the most fruitful ideas in statistical learning. This idea lies at the core of a variety of methods, from two-layer neural networks to kernel regression, to boosting. In general, the resulting risk minimization proble...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,961
2407.15196	Channel Shaping Using Beyond Diagonal Reconfigurable Intelligent Surface: Analysis, Optimization, and Enhanced Flexibility	This paper investigates the capability of a passive Reconfigurable Intelligent Surface (RIS) to redistribute the singular values of point-to-point Multiple-Input Multiple-Output (MIMO) channels for achieving power and rate gains. We depart from the conventional Diagonal (D)-RIS with diagonal phase shift matrix and adop...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	475,071
2409.12005	Representing Positional Information in Generative World Models for Object Manipulation	Object manipulation capabilities are essential skills that set apart embodied agents engaging with the world, especially in the realm of robotics. The ability to predict outcomes of interactions with objects is paramount in this setting. While model-based control methods have started to be employed for tackling manipul...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	489,397
2007.10830	CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVE	In this paper, we describe our system for Task 4 of SemEval 2020, which involves differentiating between natural language statements that confirm to common sense and those that do not. The organizers propose three subtasks - first, selecting between two sentences, the one which is against common sense. Second, identify...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	188,391
1511.00615	Optimizing the Deployment of Electric Vehicle Charging Stations Using Pervasive Mobility Data	With recent advances in battery technology and the resulting decrease in the charging times, public charging stations are becoming a viable option for Electric Vehicle (EV) drivers. Concurrently, wide-spread use of location-tracking devices in mobile phones and wearable devices makes it possible to track individual-lev...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	48,427
2208.02559	Equivalence between Time Series Predictability and Bayes Error Rate	Predictability is an emerging metric that quantifies the highest possible prediction accuracy for a given time series, being widely utilized in assessing known prediction algorithms and characterizing intrinsic regularities in human behaviors. Lately, increasing criticisms aim at the inaccuracy of the estimated predict...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	311,505
2202.01905	Modified ResNet Model for MSI and MSS Classification of Gastrointestinal Cancer	In this work, a modified ResNet model is proposed for the classification of Microsatellite instability(MSI) and Microsatellite stability(MSS) of gastrointestinal cancer. The performance of this model is analyzed and compared with existing models. The proposed model surpassed the existing models with an accuracy of 0.89...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,630
1804.10160	Two-Stream Binocular Network: Accurate Near Field Finger Detection Based On Binocular Images	Fingertip detection plays an important role in human computer interaction. Previous works transform binocular images into depth images. Then depth-based hand pose estimation methods are used to predict 3D positions of fingertips. Different from previous works, we propose a new framework, named Two-Stream Binocular Netw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,102
1803.07484	Collective Schedules: Scheduling Meets Computational Social Choice	When scheduling public works or events in a shared facility one needs to accommodate preferences of a population. We formalize this problem by introducing the notion of a collective schedule. We show how to extend fundamental tools from social choice theory---positional scoring rules, the Kemeny rule and the Condorcet ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	93,063
2312.16211	An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development	Causal networks are widely used in many fields, including epidemiology, social science, medicine, and engineering, to model the complex relationships between variables. While it can be convenient to algorithmically infer these models directly from observational data, the resulting networks are often plagued with errone...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	418,308
1612.07495	Noise Mitigation for Neural Entity Typing and Relation Extraction	In this paper, we address two different types of noise in information extraction models: noise from distant supervision and noise from pipeline input features. Our target tasks are entity typing and relation extraction. For the first noise type, we introduce multi-instance multi-label learning algorithms using neural n...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	65,949
1901.05809	On Pliable Index Coding	A new variant of index coding problem termed as Pliable Index Coding Problem (PICOD) is formulated in [S. Brahma, C. Fragouli, "Pliable index coding", IEEE Transactions on Information Theory, vol. 61, no. 11, pp. 6192-6203, 2015]. In PICOD, we consider a server holding a set of messages and there is a set of clients ha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,861
2306.03980	Counterfactual Explanations and Predictive Models to Enhance Clinical Decision-Making in Schizophrenia using Digital Phenotyping	Clinical practice in psychiatry is burdened with the increased demand for healthcare services and the scarce resources available. New paradigms of health data powered with machine learning techniques could open the possibility to improve clinical workflow in critical stages of clinical assessment and treatment in psych...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	371,552
2205.12406	Multi-Head Online Learning for Delayed Feedback Modeling	In online advertising, it is highly important to predict the probability and the value of a conversion (e.g., a purchase). It not only impacts user experience by showing relevant ads, but also affects ROI of advertisers and revenue of marketplaces. Unlike clicks, which often occur within minutes after impressions, conv...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	298,517
2407.17085	OVR: A Dataset for Open Vocabulary Temporal Repetition Counting in Videos	We introduce a dataset of annotations of temporal repetitions in videos. The dataset, OVR (pronounced as over), contains annotations for over 72K videos, with each annotation specifying the number of repetitions, the start and end time of the repetitions, and also a free-form description of what is repeating. The annot...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	475,845
1910.13728	Structure of Deep Neural Networks with a Priori Information in Wireless Tasks	Deep neural networks (DNNs) have been employed for designing wireless networks in many aspects, such as transceiver optimization, resource allocation, and information prediction. Existing works either use fully-connected DNN or the DNNs with specific structures that are designed in other domains. In this paper, we show...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	151,464
1607.03070	Forward Table-Based Presynaptic Event-Triggered Spike-Timing-Dependent Plasticity	Spike-timing-dependent plasticity (STDP) incurs both causal and acausal synaptic weight updates, for negative and positive time differences between pre-synaptic and post-synaptic spike events. For realizing such updates in neuromorphic hardware, current implementations either require forward and reverse lookup access t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	58,454
2209.06367	A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms	Understanding causality helps to structure interventions to achieve specific goals and enables predictions under interventions. With the growing importance of learning causal relationships, causal discovery tasks have transitioned from using traditional methods to infer potential causal structures from observational da...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	317,370
1111.6640	A Markov Random Field Topic Space Model for Document Retrieval	This paper proposes a novel statistical approach to intelligent document retrieval. It seeks to offer a more structured and extensible mathematical approach to the term generalization done in the popular Latent Semantic Analysis (LSA) approach to document indexing. A Markov Random Field (MRF) is presented that captures...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	13,211
1908.04149	Enabling Commercial Autonomous Space Robotic Explorers	In contrast to manned missions, the application of autonomous robots for space exploration missions decreases the safety concerns of the exploration missions while extending the exploration distance since returning transportation is not necessary for robotics missions. In addition, the employment of robots in these mis...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	141,414
1903.06727	On Sample Complexity of Projection-Free Primal-Dual Methods for Learning Mixture Policies in Markov Decision Processes	We study the problem of learning policy of an infinite-horizon, discounted cost, Markov decision process (MDP) with a large number of states. We compute the actions of a policy that is nearly as good as a policy chosen by a suitable oracle from a given mixture policy class characterized by the convex hull of a set of k...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,448
1601.05928	Role of Large Scale Channel Information on Predictive Resource Allocation	When the future achievable rate is perfectly known, predictive resource allocation can provide high performance gain over traditional resource allocation for the traffic without stringent delay requirement. However, future channel information is hard to obtain in wireless channels, especially the small-scale fading gai...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,184
1905.04445	Explaining intuitive difficulty judgments by modeling physical effort and risk	The ability to estimate task difficulty is critical for many real-world decisions such as setting appropriate goals for ourselves or appreciating others' accomplishments. Here we give a computational account of how humans judge the difficulty of a range of physical construction tasks (e.g., moving 10 loose blocks from ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	130,469
2212.13767	Learning to Detect Noisy Labels Using Model-Based Features	Label noise is ubiquitous in various machine learning scenarios such as self-labeling with model predictions and erroneous data annotation. Many existing approaches are based on heuristics such as sample losses, which might not be flexible enough to achieve optimal solutions. Meta learning based methods address this is...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	338,394
1501.05396	Deep Multimodal Learning for Audio-Visual Speech Recognition	In this paper, we present methods in deep multimodal learning for fusing speech and visual modalities for Audio-Visual Automatic Speech Recognition (AV-ASR). First, we study an approach where uni-modal deep networks are trained separately and their final hidden layers fused to obtain a joint feature space in which anot...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	39,475
2205.00191	Exploring Gender-Expansive Categorization Options for Robots	Gender is increasingly being explored as a social characteristic ascribed to robots by people. Yet, research involving social robots that may be gendered tends not to address gender perceptions, such as through pilot studies or manipulation checks. Moreover, research that does address gender perceptions has been limite...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	294,163
2006.07796	Structure by Architecture: Structured Representations without Regularization	We study the problem of self-supervised structured representation learning using autoencoders for downstream tasks such as generative modeling. Unlike most methods which rely on matching an arbitrary, relatively unstructured, prior distribution for sampling, we propose a sampling technique that relies solely on the ind...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	181,944
2208.09366	Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations	Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	313,677
2106.02126	A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms	One of the key drivers of complexity in the classical (stochastic) multi-armed bandit (MAB) problem is the difference between mean rewards in the top two arms, also known as the instance gap. The celebrated Upper Confidence Bound (UCB) policy is among the simplest optimism-based MAB algorithms that naturally adapts to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	238,736
2203.05028	Dynamic Instance Domain Adaptation	Most existing studies on unsupervised domain adaptation (UDA) assume that each domain's training samples come with domain labels (e.g., painting, photo). Samples from each domain are assumed to follow the same distribution and the domain labels are exploited to learn domain-invariant features via feature alignment. How...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,679
2309.08888	GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels	Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden. Recently, contrastive learning has exhibited a great potential in learning robust representations to boost downstream tasks with lim...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	392,367
2409.06299	Enhancing Long Video Understanding via Hierarchical Event-Based Memory	Recently, integrating visual foundation models into large language models (LLMs) to form video understanding systems has attracted widespread attention. Most of the existing models compress diverse semantic information within the whole video and feed it into LLMs for content comprehension. While this method excels in s...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	487,074
2110.05376	Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric	Measuring automatic speech recognition (ASR) system quality is critical for creating user-satisfying voice-driven applications. Word Error Rate (WER) has been traditionally used to evaluate ASR system quality; however, it sometimes correlates poorly with user perception/judgement of transcription quality. This is becau...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	260,260
1409.4826	Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits	This brief paper proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical imple...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,114
2304.12654	CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis	With growing attention to tabular data these days, the attempt to apply a synthetic table to various tasks has been expanded toward various scenarios. Owing to the recent advances in generative modeling, fake data generated by tabular data synthesis models become sophisticated and realistic. However, there still exists...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	360,308
2311.12714	Decrypting Nonlinearity: Koopman Interpretation and Analysis of Cryptosystems	Public-key cryptosystems rely on computationally difficult problems for security, traditionally analyzed using number theory methods. In this paper, we introduce a novel perspective on cryptosystems by viewing the Diffie-Hellman key exchange and the Rivest-Shamir-Adleman cryptosystem as nonlinear dynamical systems. By ...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	409,447
1003.2005	Control of Complex Maneuvers for a Quadrotor UAV using Geometric Methods on SE(3)	This paper provides new results for control of complex flight maneuvers for a quadrotor unmanned aerial vehicle (UAV). The flight maneuvers are defined by a concatenation of flight modes or primitives, each of which is achieved by a nonlinear controller that solves an output tracking problem. A mathematical model of th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	5,893
2409.10918	FSL-HDnn: A 5.7 TOPS/W End-to-end Few-shot Learning Classifier Accelerator with Feature Extraction and Hyperdimensional Computing	This paper introduces FSL-HDnn, an energy-efficient accelerator that implements the end-to-end pipeline of feature extraction, classification, and on-chip few-shot learning (FSL) through gradient-free learning techniques in a 40 nm CMOS process. At its core, FSL-HDnn integrates two low-power modules: Weight clustering ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	488,930
2102.06555	Online Graph Dictionary Learning	Dictionary learning is a key tool for representation learning, that explains the data as linear combination of few basic elements. Yet, this analysis is not amenable in the context of graph learning, as graphs usually belong to different metric spaces. We fill this gap by proposing a new online Graph Dictionary Learnin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,792
2312.14280	Fine-grained Forecasting Models Via Gaussian Process Blurring Effect	Time series forecasting is a challenging task due to the existence of complex and dynamic temporal dependencies. This can lead to incorrect predictions by even the best forecasting models. Using more training data is one way to improve the accuracy, but this source is often limited. In contrast, we are building on succ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	417,574
2203.14581	S2-Net: Self-supervision Guided Feature Representation Learning for Cross-Modality Images	Combining the respective advantages of cross-modality images can compensate for the lack of information in the single modality, which has attracted increasing attention of researchers into multi-modal image matching tasks. Meanwhile, due to the great appearance differences between cross-modality image pairs, it often f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,066
2205.00905	FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation	Graph contrastive learning (GCL), as a popular approach to graph self-supervised learning, has recently achieved a non-negligible effect. To achieve superior performance, the majority of existing GCL methods elaborate on graph data augmentation to construct appropriate contrastive pairs. However, existing methods place...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	294,419
2008.00745	Community membership consistency applied to corporate board interlock networks	Community detection is a well established method for studying the meso scale structure of social networks. Applying a community detection algorithm results in a division of a network into communities that is often used to inspect and reason about community membership of specific nodes. This micro level interpretation s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	190,098
1310.1419	On Association Cells in Random Heterogeneous Networks	Characterizing user to access point (AP) association strategies in heterogeneous cellular networks (HetNets) is critical for their performance analysis, as it directly influences the load across the network. In this letter, we introduce and analyze a class of association strategies, which we term stationary association...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	27,567
2412.13860	Domain-adaptative Continual Learning for Low-resource Tasks: Evaluation on Nepali	Continual learning has emerged as an important research direction due to the infeasibility of retraining large language models (LLMs) from scratch in the event of new data availability. Of great interest is the domain-adaptive pre-training (DAPT) paradigm, which focuses on continually training a pre-trained language mo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	518,483
2412.03517	NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images	Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data. However, existing methods depend on external multi-view alignment processes, such as explicit pose estimation or pre-reconstruction, which limits their flexibility and accessibility, especially when ali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,989
2210.01162	Learning Minimally-Violating Continuous Control for Infeasible Linear Temporal Logic Specifications	This paper explores continuous-time control synthesis for target-driven navigation to satisfy complex high-level tasks expressed as linear temporal logic (LTL). We propose a model-free framework using deep reinforcement learning (DRL) where the underlying dynamic system is unknown (an opaque box). Unlike prior work, th...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	true	321,146
2108.12173	CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation	In recent years, deep convolutional neural networks have made significant advances in pathology image segmentation. However, pathology image segmentation encounters with a dilemma in which the higher-performance networks generally require more computational resources and storage. This phenomenon limits the employment o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,417
2501.13795	Training-Free Zero-Shot Temporal Action Detection with Vision-Language Models	Existing zero-shot temporal action detection (ZSTAD) methods predominantly use fully supervised or unsupervised strategies to recognize unseen activities. However, these training-based methods are prone to domain shifts and require high computational costs, which hinder their practical applicability in real-world scena...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,826
1811.03700	A Comparison of Lattice-free Discriminative Training Criteria for Purely Sequence-Trained Neural Network Acoustic Models	In this work, three lattice-free (LF) discriminative training criteria for purely sequence-trained neural network acoustic models are compared on LVCSR tasks, namely maximum mutual information (MMI), boosted maximum mutual information (bMMI) and state-level minimum Bayes risk (sMBR). We demonstrate that, analogous to L...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	112,902
2201.04426	The Geometry of Navigation Problems	While many works exploiting an existing Lie group structure have been proposed for state estimation, in particular the Invariant Extended Kalman Filter (IEKF), few papers address the construction of a group structure that allows casting a given system into the framework of invariant filtering. In this paper we introduc...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	275,098
2008.01809	Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring	While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	190,438
1404.3638	Approximate MMSE Estimator for Linear Dynamic Systems with Gaussian Mixture Noise	In this work we propose an approximate Minimum Mean-Square Error (MMSE) filter for linear dynamic systems with Gaussian Mixture noise. The proposed estimator tracks each component of the Gaussian Mixture (GM) posterior with an individual filter and minimizes the trace of the covariance matrix of the bank of filters, as...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	32,329
1906.03944	Solving Electrical Impedance Tomography with Deep Learning	This paper introduces a new approach for solving electrical impedance tomography (EIT) problems using deep neural networks. The mathematical problem of EIT is to invert the electrical conductivity from the Dirichlet-to-Neumann (DtN) map. Both the forward map from the electrical conductivity to the DtN map and the inver...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	134,544
1907.02189	On the Convergence of FedAvg on Non-IID Data	Federated learning enables a large amount of edge computing devices to jointly learn a model without data sharing. As a leading algorithm in this setting, Federated Averaging (\texttt{FedAvg}) runs Stochastic Gradient Descent (SGD) in parallel on a small subset of the total devices and averages the sequences only once ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,548
2102.09427	Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction	Early detection of suicidal ideation in depressed individuals can allow for adequate medical attention and support, which in many cases is life-saving. Recent NLP research focuses on classifying, from a given piece of text, if an individual is suicidal or clinically healthy. However, there have been no major attempts t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	220,776
2212.12844	Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images	Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is the Gleason grading of histopathology images. The Gleason grade is assigned based on tumor architecture on Hematoxylin and Eosin (H&E) staine...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,152
2011.06844	Cross-Domain Learning for Classifying Propaganda in Online Contents	As news and social media exhibit an increasing amount of manipulative polarized content, detecting such propaganda has received attention as a new task for content analysis. Prior work has focused on supervised learning with training data from the same domain. However, as propaganda can be subtle and keeps evolving, ma...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	206,363
2309.08040	Gradient based Grasp Pose Optimization on a NeRF that Approximates Grasp Success	Current robotic grasping methods often rely on estimating the pose of the target object, explicitly predicting grasp poses, or implicitly estimating grasp success probabilities. In this work, we propose a novel approach that directly maps gripper poses to their corresponding grasp success values, without considering ob...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	392,010

Subsets and Splits

No community queries yet

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