Papers
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.
Tractable Uncertainty for Structure Learning
Benjie Wang, Matthew R Wicker, Marta Kwiatkowska
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four
Stephan Wäldchen, Sebastian Pokutta, Felix Huber
Training Discrete Deep Generative Models via Gapped Straight-Through Estimator
Ting-Han Fan, Ta-Chung Chi, Alexander I. Rudnicky et al.
Training OOD Detectors in their Natural Habitats
Julian Katz-Samuels, Julia B Nakhleh, Robert Nowak et al.
Training Your Sparse Neural Network Better with Any Mask
Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen et al.
Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval
Pascal Notin, Mafalda Dias, Jonathan Frazer et al.
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information
Mark Collier, Rodolphe Jenatton, Effrosyni Kokiopoulou et al.
Transfer Learning In Differential Privacy’s Hybrid-Model
Refael Kohen, Or Sheffet
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
Tung Nguyen, Aditya Grover
Transformer Quality in Linear Time
Weizhe Hua, Zihang Dai, Hanxiao Liu et al.