Papers
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
Peter Kairouz, Ziyu Liu, Thomas Steinke
The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu
The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling
The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen Hardy, Wilko Henecka et al.
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen et al.
The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
The Logical Options Framework
Brandon Araki, Xiao Li, Kiran Vodrahalli et al.
Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
Gen Li, Yuantao Gu
The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, Viswanath Nagarajan
The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori F Ebihara
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha et al.
Thinking Like Transformers
Gail Weiss, Yoav Goldberg, Eran Yahav
Three Operator Splitting with a Nonconvex Loss Function
Alp Yurtsever, Varun Mangalick, Suvrit Sra
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido F Montufar
Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
Gen Li, Changxiao Cai, Yuxin Chen et al.
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients
Artem Artemev, David R. Burt, Mark van der Wilk
Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz-Garcia, Ge Zhang, Samuel S Schoenholz et al.
To be Robust or to be Fair: Towards Fairness in Adversarial Training
Han Xu, Xiaorui Liu, Yaxin Li et al.
Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying et al.
Toward Better Generalization Bounds with Locally Elastic Stability
Zhun Deng, Hangfeng He, Weijie Su
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
Kaixin Wang, Kuangqi Zhou, Qixin Zhang et al.