Most Cited 2025 "over-pessimism mitigation" Papers
22,274 papers found • Page 104 of 112
Conference
Towards S²-Challenges Underlying LLM-Based Augmentation for Personalized News Recommendation
Shicheng Wang, Hengzhu Tang, Li Gao et al.
Federated Recommendation with Explicitly Encoding Item Bias
Zhihao Wang, He Bai, Wenke Huang et al.
Counterfactual Task-augmented Meta-learning for Cold-start Sequential Recommendation
Zhiqiang Wang, Jiayi Pan, Xingwang Zhao et al.
Cross-Domain Trajectory Association Based on Hierarchical Spatiotemporal Enhanced Attention Hypergraph
Chenlong Wu, Ze Wang, Keqing Cen et al.
Robust Graph Based Social Recommendation Through Contrastive Multi-View Learning
Fei Xiong, Tao Zhang, Shirui Pan et al.
KGCRR: An Effective Metric-Driven Knowledge Graph Completion Framework by Designing a Novel Upper Bound Function with Adaptive Approximation to Reciprocal Rank
Kuan Xu, Kuo Yang, Jian Liu et al.
Semantic Enhanced Heterogeneous Hypergraph Network for Collaborative Filtering
Mingtao Xu, Wei Wei, Peixuan Yang et al.
NLGT: Neighborhood-based and Label-enhanced Graph Transformer Framework for Node Classification
Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.
Reverse Region-to-Entity Annotation for Pixel-Level Visual Entity Linking
Zhengfei Xu, Sijia Zhao, Yanchao Hao et al.
Co-Progression Knowledge Distillation with Knowledge Prototype for Industrial Anomaly Detection
Bokang Yang, Zhe Zhang, Jie Ma
Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer
Jinyu Yang, Ruijia Wang, Cheng Yang et al.
Curriculum Conditioned Diffusion for Multimodal Recommendation
Yimeng Yang, Haokai Ma, Lei Meng et al.
Mind Individual Information! Principal Graph Learning for Multimedia Recommendation
Penghang Yu, Zhiyi Tan, Guanming Lu et al.
Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection
Zhizhi Yu, Chundong Liang, Xinglong Chang et al.
Fuzzy Collaborative Reasoning
Huanhuan Yuan, Pengpeng Zhao, Jiaqing Fan et al.
Fast Track to Winning Tickets: Repowering One-Shot Pruning for Graph Neural Networks
Yanwei Yue, Guibin Zhang, Haoran Yang et al.
Core Knowledge Learning Framework for Graph
Bowen Zhang, Zhichao Huang, Guangning Xu et al.
DREAM: Decoupled Discriminative Learning with Bigraph-aware Alignment for Semi-supervised 2D-3D Cross-modal Retrieval
Fan Zhang, Changhu Wang, Zebang Cheng et al.
Expand Horizon: Graph Out-of-Distribution Generalization via Multi-Level Environment Inference
Jiaqiang Zhang, Songcan Chen
Lightweight Yet Fine-Grained: A Graph Capsule Convolutional Network with Subspace Alignment for Shared-Account Sequential Recommendation
Jinyu Zhang, Zhongying Zhao, Chao Li et al.
Trigger3:Refining Query Correction via Adaptive Model Selector
Kepu Zhang, Zhongxiang Sun, Xiao Zhang et al.
Integrating Large Language Models and Möbius Group Transformations for Temporal Knowledge Graph Embedding on the Riemann Sphere
Sensen Zhang, Xun Liang, Simin Niu et al.
A Lightweight Sparse Interaction Network for Time Series Forecasting
Xu Zhang, Qitong Wang, Peng Wang et al.
Highly Imperceptible Black-Box Graph Injection Attacks with Reinforcement Learning
Maochang Zhao, Jing Zhang
Neighborhood-Aware Negative Sampling for Student Knowledge and Behavior Modeling
Siqian Zhao, Sherry Sahebi
TRACI: A Data-centric Approach for Multi-Domain Generalization on Graphs
Yusheng Zhao, Changhu Wang, Xiao Luo et al.
Dynamic Spectral Graph Anomaly Detection
Jianbo Zheng, Chao Yang, Tairui Zhang et al.
The Adaptive Q-Network for Recommendation Tasks with Dynamic Item Space
Jianxiang Zhu, Dandan Lai, Zhongcui Ma et al.
Representation Learning Based Predicate Invention on Knowledge Graphs
Man Zhu, Pengfei Huang, Lei Gu et al.
Ghidorah: Towards Robust Multi-Scale Information Diffusion Prediction via Test-Time Training
Wenting Zhu, Chaozhuo Li, Litian Zhang et al.
Refine then Classify: Robust Graph Neural Networks with Reliable Neighborhood Contrastive Refinement
Shuman Zhuang, Zhihao Wu, Zhaoliang Chen et al.
Merging Mechanisms for Ads and Organic Items in E-commerce Platforms
Nan An, Weian Li, Qi Qi et al.
Fair Division via the Cake-Cutting Share
Yannan Bai, Kamesh Munagala, Yiheng Shen et al.
Multi-Robot Task Allocation Using Global Games with Negative Feedback: The Colony Maintenance Problem
Logan E. Beaver
The Distortion of Public-Spirited Participatory Budgeting
Mark Bedaywi, Bailey Flanigan, Mohamad Latifian et al.
Optimal Auction Design for Mixed Bidders
Xiaohui Bei, Pinyan Lu, Zhiqi Wang et al.
Nearly Tight Bounds on Approximate Equilibria in Spatial Competition on the Line
Umang Bhaskar, Soumyajit Pyne
Beyond Monotonicity: On the Convergence of Learning Algorithms in Standard Auction Games
Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner et al.
Weak Strategyproofness in Randomized Social Choice
Felix Brandt, Patrick Lederer
Welfare-Optimal Serial Dictatorships Have Polynomial Query Complexity
Ioannis Caragiannis, Kurt Mehlhorn, Nidhi Rathi
Mechanism Design for Connecting Regions Under Disruptions
Hau Chan, Jianan Lin, Zining Qin et al.
Online Learning of Coalition Structures by Selfish Agents
Saar Cohen, Noa Agmon
Bounded Rationality Equilibrium Learning in Mean Field Games
Yannick Eich, Christian Fabian, Kai Cui et al.
Verifying Proportionality in Temporal Voting
Edith Elkind, Svetlana Obraztsova, Jannik Peters et al.
Robust Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents
Seyed A. Esmaeili, Suho Shin, Aleksandrs Slivkins
Individually Stable Dynamics in Coalition Formation over Graphs
Angelo Fanelli, Laurent Gourvès, Ayumi Igarashi et al.
Forecasting Competitions with Correlated Events
Rafael Frongillo, Manuel Lladser, Anish Thilagar et al.
TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning
Gangqiang Hu, Jianfeng Lu, Jianmin Han et al.
Learning Optimal Auctions with Correlated Value Distributions
Da Huo, Zhenzhe Zheng, Fan Wu
Metric Distortion of Line-up Elections: The Right Person for the Right Job
Christopher Jerrett, Yue Han, Elliot Anshelevich
Sample Complexity of Linear Regression Models for Opinion Formation in Networks
Haolin Liu, Rajmohan Rajaraman, Ravi Sundaram et al.
Decentralized Convergence to Equilibrium Prices in Trading Networks
Edwin Lock, Benjamin Patrick Evans, Eleonora Kreacic et al.
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
Mary Monroe, Anish Thilagar, Melody Hsu et al.
Voter Priming Campaigns: Strategies, Equilibria, and Algorithms
Jonathan Shaki, Yonatan Aumann, Sarit Kraus
A Unified Model of Direct and Indirect Reciprocity in Multichannel Games
Juan Shi, Zhaoheng Cao, Jinzhuo Liu et al.
Uncommon Belief in Rationality
Qi Shi, Pavel Naumov
Achieving Balanced Representation in School Choice with Diversity Goals
Zhaohong Sun, Makoto Yokoo
Paid with Models: Optimal Contract Design for Collaborative Machine Learning
Bingchen Wang, Zhaoxuan Wu, Fusheng Liu et al.
Deviate or Not: Learning Coalition Structures with Multiple-bit Observations in Games
Yixuan Even Xu, Zhe Feng, Fei Fang
Interpretable Solutions for Multi-Physics PDEs Using T-NNGP
Lulu Cao, Zexin Lin, Kay Chen Tan et al.
Cognitive Fluctuations Enhanced Attention Network for Knowledge Tracing
Mingliang Hou, Xueyi Li, Teng Guo et al.
AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Feature Space-Guided Inversion
Chenqi Li, Boyan Gao, Gabriel Davis Jones et al.
Label Aggregation for Composite Crowd Tasks by Worker Ability Constraint Satisfaction
Jiyi Li
HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units
Guorui Liao, Chunyuan Zheng, Li Cheng et al.
Optimal and Efficient Binary Questioning for Accelerated Annotation
Franco Marchesoni-Acland, Jean-Michel Morel, Josselin Kherroubi et al.
Breaking Data Silos in Parkinson’s Disease Diagnosis: An Adaptive Federated Learning Approach for Privacy-Preserving Facial Expression Analysis
Meng Pang, Houwei Xu, Zheng Huang et al.
Learning Visually Grounded Domain Ontologies via Embodied Conversation and Explanation
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
DeCorrNet: Enhancing Neural Decoding Performance by Eliminating Correlations in Noise
Xianhan Tan, Yu Qi, Yueming Wang
Manhattan Self-Attention Diffusion Residual Networks with Dynamic Bias Rectification for BCI-based Few-Shot Learning
Hao Wang, Li Xu, Yuntao Yu et al.
MindPainter: Efficient Brain-Conditioned Painting of Natural Images via Cross-Modal Self-Supervised Learning
Muzhou Yu, Shuyun Lin, Hongwei Yan et al.
CollageNoter: Real-Time and Adaptive Collage Layout Design for Screenshot-Based E-Note-Taking
Qiuyun Zhang, Bin Guo, Lina Yao et al.
Learning to Collaborate with Unknown Agents in the Absence of Reward
Zuyuan Zhang, Hanhan Zhou, Mahdi Imani et al.
Hierarchical Multi-Source Uncertainty Aggregation for Interactive Video Captioning
Ervine Zheng, Qi Yu
Integrating Inference and Experimental Design for Contextual Behavioral Model Learning
Gongtao Zhou, Haoran Yu
GNN-Transformer Task Planning Enhanced with Semantic-Driven Data Augmentation
Soojin Jeong, Seongwan Byeon, Sangwoo Kim et al.
Multi-fingered Hand Grasps with Visuo-Tactile Fusion via Multi-Agent Deep Reinforcement Learning
Peida Jia, Xuanheng Li, Tianqiang Zhu et al.
Heterogeneous Multi-Robot Graph Coverage with Proximity and Movement Constraints
Dolev Mutzari, Yonatan Aumann, Sarit Kraus
Evolutionary Reinforcement Learning with Parameterized Action Primitives for Diverse Manipulation Tasks
Xianxu Qiu, Haiming Huang, Weiwei Chen et al.
BEVSync: Asynchronous Data Alignment for Camera-based Vehicle-Infrastructure Cooperative Perception Under Uncertain Delays
Wentao Wang, Jiaqian Wang, Yuxin Deng et al.
GMAP: Generalized Manipulation of Articulated Objects in Robotic Using Pre-trained Model
Hongliang Zeng, Ping Zhang, Fang Li et al.
ASP-Driven Emergency Planning for Norm Violations in Reinforcement Learning
Sebastian Adam, Thomas Eiter
Minimal Change in Modal Logic S5
Carlos Aguilera-Ventura, Jonathan Ben-Naim, Andreas Herzig
Fast Computing of Dung Semantics in Acyclic Probabilistic Argumentation Frameworks
Stefano Bistarelli, Victor David, Pierre Monnin et al.
Answering Conjunctive Queries with Safe Negation and Inequalities over RDFS Knowledge Bases
Gianluca Cima, Marco Console, Roberto Maria Delfino et al.
Germane Conflicts: Desirable Properties for Localising Inconsistency
Glauber de Bona, Anthony Hunter
Situation Calculus Temporally Lifted Abstractions for Generalized Planning
Giuseppe de Giacomo, Yves Lespérance, Matteo Mancanelli
A Computationally Grounded Framework for Cognitive Attitudes
Tiago de Lima, Emiliano Lorini, Elise Perrotin et al.
Sound Over-Approximation of Equational Reasoning with Variable-Preserving Rules Parameterized by Derivation Depth
Mateus de Oliveira Oliveira
Solving Epistemic Logic Programs Using Generate-and-Test with Propagation
Jorge Fandinno, Lute Lillo
On the Logic of Theory Base Change: Reformulation of Belief Bases
Eduardo L. Fermé, Andreas Herzig, Maria Vanina Martinez
LTLf Synthesis Under Unreliable Input
Christian Hagemeier, Giuseppe de Giacomo, Moshe Y. Vardi
New Compilation Languages Based on Restricted Weak Decomposability
Petr Illner
Hybrid Reasoning About Relative Position and Orientation of Objects and Navigating Agents Using Answer Set Programming
Yusuf Izmirlioglu
APKGC: Noise-enhanced Multi-Modal Knowledge Graph Completion with Attention Penalty
Yue Jian, Xiangyu Luo, Zhifei Li et al.
A Modal Logic for Joint Abilities of Structured Strategies with Bounded Complexity
Ruiqi Jin, Yongmei Liu, Liping Xiong
On Action Theories with Iterable First-Order Progression
Daxin Liu, Jens Claßen
Spectra of Cardinality Queries over Description Logic Knowledge Bases
Quentin Manière, Marcin Przybyłko
Temporal Specification Optimisation for the Event Calculus
Periklis Mantenoglou, Alexander Artikis
Consistent Query Answering over Existential Rules with Open and Closed Predicates
Lorenzo Marconi, Riccardo Rosati
Probabilistic Strategy Logic with Degrees of Observability
Chunyan Mu, Nima Motamed, Natasha Alechina et al.
Tensor Decomposition Meets Knowledge Compilation: A Study Comparing Tensor Trains with OBDDs
Ryoma Onaka, Kengo Nakamura, Masaaki Nishino et al.
A Logical Analysis of Hanabi
Elise Perrotin
Checking Consistency of CP-Theory Preferences in Polynomial Time
Erik Rauer, Samik Basu, Vasant Honavar
Shield Synthesis for LTL Modulo Theories
Andoni Rodríguez, Guy Amir, Davide Corsi et al.
A Variable Occurrence-Centric Framework for Inconsistency Handling
Yakoub Salhi
Learning Theorem Rationale for Improving the Mathematical Reasoning Capability of Large Language Models
Yu Sheng, Linjing Li, Daniel Dajun Zeng
SR-FoT: A Syllogistic-Reasoning Framework of Thought for Large Language Models Tackling Knowledge-based Reasoning Tasks
Wentao Wan, Zhuojie Yang, Yongcan Chen et al.
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
Yajing Wang, Zongwei Luo, Jingzhe Wang et al.
Temporal Conjunctive Query Answering via Rewriting
Lukas Westhofen, Jean Christoph Jung, Daniel Neider
SPAC: Sparse Partitioning and Adaptive Core Tensor Pruning Model for Knowledge Graph Completion
Chuhong Yang, Bin Li, Nan Wu
What Is a Good Question? Assessing Question Quality via Meta-Fact Checking
Bo Zhang, Jianghua Zhu, Chaozhuo Li et al.
A Theory of Formalisms for Representing Knowledge
Heng Zhang, Guifei Jiang, Donghui Quan
Counterfactual Debiasing for Physical Audiovisual Commonsense Reasoning
Daoming Zong, Chaoyue Ding, Kaitao Chen et al.
Exponential-Family Harmoniums with Neural Sufficient Statistics
Azwar Abdulsalam, Joseph G. Makin
Improving Deep Learning Speed and Performance Through Synaptic Neural Balance
Antonios Alexos, Ian Domingo, Pierre Baldi
Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data
Bailey Andrew, David R. Westhead, Luisa Cutillo
Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady
List Update with Prediction
Yossi Azar, Shahar Lewkowicz, Varun Suriyanarayana
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity
Hongyan Bao, Pengwen Chen, Ying Sun et al.
Deep-Union Completion
Siddharth Baskar, Karan Vikyath Veeranna Rupashree, Daniel L. Pimentel-Alarcón
A (1+ε)-Approximation for Ultrametric Embedding in Subquadratic Time
Gabriel Bathie, Guillaume Lagarde
Generalized Convergence Analysis of Tsetlin Automaton Based Algorithms: A Probabilistic Approach to Concept Learning
Mohamed-Bachir Belaid, Jivitesh Sharma, Lei Jiao et al.
Teaching Models to Improve on Tape
Liat Bezalel, Eyal Orgad, Amir Globerson
Learnability of Parameter-Bounded Bayes Nets
Arnab Bhattacharyya, Davin Choo, Sutanu Gayen et al.
Neural Conjugate Flows: A Physics-Informed Architecture with Flow Structure
Arthur Bizzi, Lucas Nissenbaum, João M. Pereira
Weighted Embeddings for Low-Dimensional Graph Representation
Thomas Bläsius, Jean-Pierre von der Heydt, Maximilian Katzmann et al.
Efficient Anomaly Detection of Irregular Sequences in Ct-Echo Model Space
Ao Chen, Xiren Zhou, Huanhuan Chen
Biased Incomplete Multi-View Learning
Haishun Chen, Cai Xu, Ziyu Guan et al.
Semi-Supervised Multimodal Classification Through Learning from Modal and Strategic Complementarities
Junchi Chen, Richong Zhang, Junfan Chen
Learnware Specification via Label-Aware Neural Embedding
Wei Chen, Jun-Xiang Mao, Min-Ling Zhang
The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards
Xi Chen, Zhihui Zhu, Andrew Perrault
Beyond Homophily: Graph Contrastive Learning with Macro-Micro Message Passing
Yiyuan Chen, Donghai Guan, Weiwei Yuan et al.
GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling
Yujie Chen, Wenhui Wu, Le Ou-Yang et al.
WatE: A Wasserstein t-distributed Embedding Method for Information-enriched Graph Visualization
Minjie Cheng, Dixin Luo, Hongteng Xu
Deep Implicit Imitation Reinforcement Learning in Heterogeneous Action Settings
Iason Chrysomallis, Georgios Chalkiadakis, Ioannis Papamichail et al.
Few-Shot Audio-Visual Class-Incremental Learning with Temporal Prompting and Regularization
Yawen Cui, Li Liu, Zitong Yu et al.
Creating Coherence in Federated Non-Negative Matrix Factorization
Sebastian Dalleiger, Aristides Gionis
Federated Binary Matrix Factorization Using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
Skill Disentanglement in Reproducing Kernel Hilbert Space
Vedant Dave, Elmar Rueckert
Expected Hypervolume Improvement Is a Particular Hypervolume Improvement
Jingda Deng, Jianyong Sun, Qingfu Zhang et al.
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data
Shilong Deng, Zetao Zheng, Hongcai He et al.
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?
Wenjun Ding, Ying An, Lixing Chen et al.
Beyond Mandatory Federations: Balancing Egoism, Utilitarianism and Egalitarianism in Mixed-Motive Games
Shaokang Dong, Chao Li, Shangdong Yang et al.
AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints
Zhiwei Dong, Mingzhu Shen, Shihao Bai et al.
Contrastive Auxiliary Learning with Structure Transformation for Heterogeneous Graphs
Wei Du, Hongmin Sun, Hang Gao et al.
Proportionally Fair Matching via Randomized Rounding
Sharmila Duppala, Nathaniel Grammel, Juan Luque et al.
Linking Industry Sectors and Financial Statements: A Hybrid Approach for Company Classification
Guy Stephane Waffo Dzuyo, Gaël Guibon, Christophe Cerisara et al.
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
Ahmad Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning
Wenzhe Fan, Zishun Yu, Chengdong Ma et al.
3SAT: A Simple Self-Supervised Adversarial Training Framework
Jiang Fang, Haonan He, Jiyan Sun et al.
Rapid Learning in Constrained Minimax Games with Negative Momentum
Zijian Fang, Zongkai Liu, Chao Yu et al.
Learning Nash Equilibrium of Markov Potential Games with a Shared Constraint via Primal-Dual Optimization
Songtao Feng, Michael Dorothy, Jie Fu
Scalable Federated One-Step Multi-View Clustering with Tensorized Regularization
Wei Feng, Danting Liu, Qianqian Wang et al.
Incremental Nyström-based Multiple Kernel Clustering
Yu Feng, Weixuan Liang, Xinhang Wan et al.
A Unifying Information-theoretic Perspective on Evaluating Generative Models
Alexis Fox, Samarth Swarup, Abhijin Adiga
Accurate Estimation of Feature Importance Faithfulness for Tree Models
Mateusz Gajewski, Adam Karczmarz, Mateusz Rapicki et al.
QuARF: Quality-Adaptive Receptive Fields for Degraded Image Perception
Fei Gao, Ying Zhou, Ziyun Li et al.
Multimodal Fusion Using Multi-View Domains for Data Heterogeneity in Federated Learning
Min Gao, Haifeng Zheng, Xinxin Feng et al.
Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning
Zijian Gao, Shanhao Han, Xingxing Zhang et al.
An Optimal Transport-based Latent Mixer for Robust Multi-modal Learning
Fengjiiao Gong, Angxiao Yue, Hongteng Xu
Conformal Prediction for Partial Label Learning
Xiuwen Gong, Nitin Bisht, Guandong Xu
Efficient Graph Bandit Learning with Side-Observations and Switching Constraints
Xueping Gong, Jiheng Zhang
Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs
Tony Gracious, Arman Gupta, Ambedkar Dukkipati
Heterogeneous Graph Neural Network on Semantic Tree
Mingyu Guan, Jack W Stokes, Qinlong Luo et al.
Enhancing Multivariate Time-Series Domain Adaptation via Contrastive Frequency Graph Discovery and Language-Guided Adversary Alignment
Haoren Guo, Haiyue Zhu, Jiahui Wang et al.
Federated Causally Invariant Feature Learning
Xianjie Guo, Kui Yu, Lizhen Cui et al.
CFDM: Contrastive Fusion and Disambiguation for Multi-View Partial-Label Learning
Qiuru Hai, Yongjian Deng, Yuena Lin et al.
Who’s the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration
Karina Halevy, Karly Hou, Charumathi Badrinath
DrugHash: Hashing Based Contrastive Learning for Virtual Screening
Jin Han, Yun Hong, Wu-Jun Li
Scalable Acceleration for Classification-Based Derivative-Free Optimization
Tianyi Han, Jingya Li, Zhipeng Guo et al.
DCHM: Dynamic Collaboration of Heterogeneous Models Through Isomerism Learning in a Blockchain-Powered Federated Learning Framework
Zhihao Hao, Bob Zhang, Haisheng Li
Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation
Qiuyan He, Minghua Deng
CAMH: Advancing Model Hijacking Attack in Machine Learning
Xing He, Jiahao Chen, Yuwen Pu et al.
Highly Parallelized Reinforcement Learning Training with Relaxed Assignment Dependencies
Zhouyu He, Peng Qiao, Rongchun Li et al.
Bi-Level Optimization for Semi-Supervised Learning with Pseudo-Labeling
Marzi Heidari, Yuhong Guo
Data Augmentation for Instruction Following Policies via Trajectory Segmentation
Niklas Hoepner, Ilaria Tiddi, Herke van Hoof
KernelMatmul: Scaling Gaussian Processes to Large Time Series
Tilman Hoffbauer, Holger H. Hoos, Jakob Bossek
Multimodal Promptable Token Merging for Diffusion Models
Cheng-Yao Hong, Tyng-Luh Liu
Adaptive Multimodal Fusion: Dynamic Attention Allocation for Intent Recognition
Bo Hu, Kai Zhang, Yanghai Zhang et al.
Unsupervised Kernel-based Multi-view Feature Selection with Robust Self-representation and Binary Hashing
Rongyao Hu, Jiangzhang Gan, Mengmeng Zhan et al.
Transfer Learning Meets Functional Linear Regression: No Negative Transfer Under Posterior Drift
Xiaoyu Hu, Zhenhua Lin
R-DTI: Drug Target Interaction Prediction Based on Second-Order Relevance Exploration
Yang Hua, Tianyang Xu, Xiaoning Song et al.
TinyFoA: Memory Efficient Forward-Only Algorithm for On-Device Learning
Baichuan Huang, Amir Aminifar
Multi-view Evidential Learning-based Medical Image Segmentation
Chao Huang, Yushu Shi, Waikeung Wong et al.
GBRIP: Granular Ball Representation for Imbalanced Partial Label Learning
Jintao Huang, Yiu-ming Cheung, Chi-man Vong et al.
Analytical-Chemistry-Informed Transformer for Infrared Spectra Modeling
Shiluo Huang, Yining Jin, Wei Jin et al.
GapMatch: Bridging Instance and Model Perturbations for Enhanced Semi-Supervised Medical Image Segmentation
Wei Huang, Lei Zhang, Zizhou Wang et al.
SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression
Xinhao Huang, You-Liang Huang, Zeyi Wen
Approximate State Abstraction for Markov Games
Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
Discovering Options That Minimize Average Planning Time
Alexander Ivanov, Akhil Bagaria, George Konidaris
TAIL-MIL: Time-Aware and Instance-Learnable Multiple Instance Learning for Multivariate Time Series Anomaly Detection
Jaeseok Jang, Hyuk-Yoon Kwon
Association Pattern-enhanced Molecular Representation Learning
Lingxiang Jia, Yuchen Ying, Tian Qiu et al.
Balancing Privacy and Performance: A Many-in-One Approach for Image Anonymization
Xuemei Jia, Jiawei Du, Hui Wei et al.
Collaborative Similarity Fusion and Consistency Recovery for Incomplete Multi-view Clustering
Bingbing Jiang, Chenglong Zhang, Xinyan Liang et al.
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
Nan Jiang, Md Nasim, Yexiang Xue
M3Net: Efficient Time-Frequency Integration Network with Mirror Attention for Audio Classification on Edge
Xuanming Jiang, Baoyi An, Guoshuai Zhao et al.
IsUMap: Manifold Learning and Data Visualization Leveraging Vietoris-Rips Filtrations
Parvaneh Joharinad, Hannaneh Fahimi, Lukas Silvester Barth et al.
Discovering Symmetries of ODEs by Symbolic Regression
Paul Kahlmeyer, Niklas Merk, Joachim Giesen
AudioGenX: Explainability on Text-to-Audio Generative Models
Hyunju Kang, Geonhee Han, Yoonjae Jeong et al.
GenPlan: Generative Sequence Models as Adaptive Planners
Akash Karthikeyan, Yash Vardhan Pant