Papers
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.
Transformers are Meta-Reinforcement Learners
Luckeciano C Melo
Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots
Tanmay Shankar, Yixin Lin, Aravind Rajeswaran et al.
Translatotron 2: High-quality direct speech-to-speech translation with voice preservation
Ye Jia, Michelle Tadmor Ramanovich, Tal Remez et al.
TSPipe: Learn from Teacher Faster with Pipelines
Hwijoon Lim, Yechan Kim, Sukmin Yun et al.
TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm
Yi Hao, Ayush Jain, Alon Orlitsky et al.
UAST: Uncertainty-Aware Siamese Tracking
Dawei Zhang, Yanwei Fu, Zhonglong Zheng
Unaligned Supervision for Automatic Music Transcription in The Wild
Ben Maman, Amit H Bermano
Uncertainty Modeling in Generative Compressed Sensing
Yilang Zhang, Mengchu Xu, Xiaojun Mao et al.
UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees
Kimon Antonakopoulos, Dong Quan Vu, Volkan Cevher et al.
Understanding and Improving Knowledge Graph Embedding for Entity Alignment
Lingbing Guo, Qiang Zhang, Zequn Sun et al.
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Xinwei Zhang, Xiangyi Chen, Mingyi Hong et al.
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Saunshi, Jordan Ash, Surbhi Goel et al.
Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information
Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta
Understanding Doubly Stochastic Clustering
Tianjiao Ding, Derek Lim, Rene Vidal et al.
Understanding Gradient Descent on the Edge of Stability in Deep Learning
Sanjeev Arora, Zhiyuan Li, Abhishek Panigrahi