Papers
11,955 papers found
TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization
Xiang Li, Junchi YANG, Niao He
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
Zeyu Tang, Yatong Chen, Yang Liu et al.
TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
Siheng Xiong, Yuan Yang, Faramarz Fekri et al.
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
Haixu Wu, Tengge Hu, Yong Liu et al.
Time to augment self-supervised visual representation learning
Arthur Aubret, Markus R. Ernst, Céline Teulière et al.
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
Jinhyung Park, Chenfeng Xu, Shijia Yang et al.
Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints
David Henry Mguni, Aivar Sootla, Juliusz Krzysztof Ziomek et al.
Toeplitz Neural Network for Sequence Modeling
Zhen Qin, Xiaodong Han, Weixuan Sun et al.
Token Merging: Your ViT But Faster
Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai et al.
Topology-aware Robust Optimization for Out-of-Distribution Generalization
Fengchun Qiao, Xi Peng
Toward Adversarial Training on Contextualized Language Representation
Hongqiu Wu, Yongxiang Liu, Hanwen Shi et al.
Towards Addressing Label Skews in One-Shot Federated Learning
Yiqun Diao, Qinbin Li, Bingsheng He
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Zhijian Zhuo, Yifei Wang, Jinwen Ma et al.
Towards Better Selective Classification
Leo Feng, Mohamed Osama Ahmed, Hossein Hajimirsadeghi et al.
Towards convergence to Nash equilibria in two-team zero-sum games
Fivos Kalogiannis, Ioannis Panageas, Emmanouil-Vasileios Vlatakis-Gkaragkounis
Towards Effective and Interpretable Human-Agent Collaboration in MOBA Games: A Communication Perspective
Yiming Gao, Feiyu Liu, Liang Wang et al.
Towards Inferential Reproducibility of Machine Learning Research
Michael Hagmann, Philipp Meier, Stefan Riezler
Towards Interpretable Deep Reinforcement Learning with Human-Friendly Prototypes
Eoin M. Kenny, Mycal Tucker, Julie Shah
Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection
Xu Zhang, Yuan Zhao, Ziang Cui et al.
Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs
Pihe Hu, Yu Chen, Longbo Huang
Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case
Runzhong Wang, Li Shen, Yiting Chen et al.
Towards Open Temporal Graph Neural Networks
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
Towards Robustness Certification Against Universal Perturbations
Yi Zeng, Zhouxing Shi, Ming Jin et al.
Towards Robust Object Detection Invariant to Real-World Domain Shifts
Qi Fan, Mattia Segu, Yu-Wing Tai et al.
Towards Smooth Video Composition
Qihang Zhang, Ceyuan Yang, Yujun Shen et al.