Papers
The Primacy Bias in Deep Reinforcement Learning
Evgenii Nikishin, Max Schwarzer, Pierluca D’Oro et al.
The Role of Deconfounding in Meta-learning
Yinjie Jiang, Zhengyu Chen, Kun Kuang et al.
The State of Sparse Training in Deep Reinforcement Learning
Laura Graesser, Utku Evci, Erich Elsen et al.
The Teaching Dimension of Regularized Kernel Learners
Hong Qian, Xu-Hui Liu, Chen-Xi Su et al.
The Unsurprising Effectiveness of Pre-Trained Vision Models for Control
Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam et al.
Thompson Sampling for (Combinatorial) Pure Exploration
Siwei Wang, Jun Zhu
Thompson Sampling for Robust Transfer in Multi-Task Bandits
Zhi Wang, Chicheng Zhang, Kamalika Chaudhuri
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points
Yi Wang, Zhiren Wang
Thresholded Lasso Bandit
Kaito Ariu, Kenshi Abe, Alexandre Proutiere
Tight and Robust Private Mean Estimation with Few Users
Shyam Narayanan, Vahab Mirrokni, Hossein Esfandiari
Time Is MattEr: Temporal Self-supervision for Video Transformers
Sukmin Yun, Jaehyung Kim, Dongyoon Han et al.
Topology-aware Generalization of Decentralized SGD
Tongtian Zhu, Fengxiang He, Lan Zhang et al.
Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning
Sixing Yu, Arya Mazaheri, Ali Jannesari
To Smooth or Not? When Label Smoothing Meets Noisy Labels
Jiaheng Wei, Hangyu Liu, Tongliang Liu et al.
Toward Compositional Generalization in Object-Oriented World Modeling
Linfeng Zhao, Lingzhi Kong, Robin Walters et al.
Towards Coherent and Consistent Use of Entities in Narrative Generation
Pinelopi Papalampidi, Kris Cao, Tomas Kocisky
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran et al.
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
Sharan Vaswani, Benjamin Dubois-Taine, Reza Babanezhad
Towards Scaling Difference Target Propagation by Learning Backprop Targets
Maxence M Ernoult, Fabrice Normandin, Abhinav Moudgil et al.
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs
Jie Ren, Mingjie Li, Meng Zhou et al.
Towards understanding how momentum improves generalization in deep learning
Samy Jelassi, Yuanzhi Li
Towards Understanding Sharpness-Aware Minimization
Maksym Andriushchenko, Nicolas Flammarion
Towards Uniformly Superhuman Autonomy via Subdominance Minimization
Brian Ziebart, Sanjiban Choudhury, Xinyan Yan et al.
TPC: Transformation-Specific Smoothing for Point Cloud Models
Wenda Chu, Linyi Li, Bo Li
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems
Manuel Brenner, Florian Hess, Jonas M Mikhaeil et al.