Papers
Towards Better Robust Generalization with Shift Consistency Regularization
Shufei Zhang, Zhuang Qian, Kaizhu Huang et al.
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu et al.
Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han et al.
Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo et al.
Towards Domain-Agnostic Contrastive Learning
Vikas Verma, Thang Luong, Kenji Kawaguchi et al.
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Muhammad A Rahman, Niklas Hopner, Filippos Christianos et al.
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu, Hengrui Zhang, Xiaofeng Gao et al.
Towards Practical Mean Bounds for Small Samples
My Phan, Philip Thomas, Erik Learned-Miller
Towards Rigorous Interpretations: a Formalisation of Feature Attribution
Darius Afchar, Vincent Guigue, Romain Hennequin
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal et al.
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
Yujia Jin, Aaron Sidford
Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency et al.
Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Mohammad Emtiyaz et al.
Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze et al.
Training Data Subset Selection for Regression with Controlled Generalization Error
Durga S, Rishabh Iyer, Ganesh Ramakrishnan et al.
Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem et al.
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Burak Bartan, Mert Pilanci
Training Recurrent Neural Networks via Forward Propagation Through Time
Anil Kag, Venkatesh Saligrama
Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Trajectory Diversity for Zero-Shot Coordination
Andrei Lupu, Brandon Cui, Hengyuan Hu et al.
Transfer-Based Semantic Anomaly Detection
Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen et al.
Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach