Papers
Re-architecting Personalized Federated Learning for Demanding Edge Environments
Quyang Pan, Sheng Sun, Tingting Wi et al.
Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time
Junjun Pan, Yixin Liu, Chuan Zhou et al.
OPTION: An Online Pricing Strategy for Asynchronous Federated Learning Against Free-Riding Attacks
Bangqi Pan, Jianfeng Lu, Shuqin Cao et al.
Policy Newton Methods for Distortion Riskmetrics
Soumen Pachal, Mizhaan Prajit Maniyar, Prashanth L. A.
Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN
Kaichen Ouyang, Zong Ke, Shengwei Fu et al.
DisCo DETR: Distance-aware Multi-view Contrastive Learning for DETR Pre-training
Chao Ouyang, Yuyang Bai, Jun Zhang et al.
ParaDySe: A Parallel Strategy Switching Framework for Dynamic Sequences in Transformer-based Large Language Models
Zhixin Ou, Peng Liang, Linbo Qiao et al.
The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms
Hikari Otsuka, Daiki Chijiwa, Yasuyuki Okoshi et al.
Large Language Models Meet Extreme Multi-label Classification: Scaling and Multi-modal Framework
Diego Ortego, Marlon Rodríguez, Mario Almagro et al.
Computing Probabilistic Explanations for ML Models: Fixed-Parameter Algorithms
Sebastian Ordyniak, Mateusz Rychlicki, Stefan Szeider
Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning
Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola et al.
Task Prototype-Based Knowledge Retrieval for Multi-Task Learning from Partially Annotated Data
Youngmin Oh, Hyung-Il Kim, Jung Uk Kim
FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification
YongKyung Oh, Dong-Young Lim, Sungil Kim
Object-Centric World Models for Causality-Aware Reinforcement Learning
Yosuke Nishimoto, Takashi Matsubara
Mitigating Endogenous Confirmation Bias in Noisy Label Learning for Vision-Language Models
Feiyang Ning, Xinyang Chen
AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation
Stephen Ni-Hahn, Rico Zhu, Jerry Yin et al.
Disentangled Generation-Based Prototypical Alignment for Few-Shot Unsupervised Domain Adaptation in Graph-Level Anomaly Detection
Zhibin Ni, Chenghao Zhang, Hai Wan et al.
PKR-QA: A Benchmark for Procedural Knowledge Reasoning with Knowledge Module Learning
Thanh-Son Nguyen, Hong Yang, Tzeh Yuan Neoh et al.
Provably Data-Driven Projection Method for Quadratic Programming
Anh Tuan Nguyen, Viet Anh Nguyen
Hexaïssa: Standing on Giants’ Shoulders—Routing the Best Chess Engines with Mixture-of-Experts and Latent Reward Learning
Bach Ngo, Nguyen Hoang Khoi Do
Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
Rashmeet Kaur Nayyar, Naman Shah, Siddharth Srivastava
GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance
Jiří Navrátil, Jarret Ross, Payel Das et al.
Policy Search, Retrieval, and Composition via Task Similarity in Collaborative Agentic Systems
Saptarshi Nath, Christos Peridis, Eseoghene Benjamin et al.
Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learning
Ankur Naskar, Gugan Thoppe, Vijay Gupta
RankList – a Listwise Preference Learning Framework for Predicting Subjective Preferences
Abinay Reddy Naini, Fernando Diaz, Carlos Busso