Papers
The Dormant Neuron Phenomenon in Deep Reinforcement Learning
Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro et al.
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick
Pierre Harvey Richemond, Allison Tam, Yunhao Tang et al.
The Fast Johnson-Lindenstrauss Transform Is Even Faster
Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
Shayne Longpre, Le Hou, Tu Vu et al.
The Hessian perspective into the Nature of Convolutional Neural Networks
Sidak Pal Singh, Thomas Hofmann, Bernhard Schölkopf
The Ideal Continual Learner: An Agent That Never Forgets
Liangzu Peng, Paris Giampouras, Rene Vidal
The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics
Aamal Hussain, Francesco Belardinelli, Dario Paccagnan
The Monge Gap: A Regularizer to Learn All Transport Maps
Théo Uscidda, Marco Cuturi
The Numerical Stability of Hyperbolic Representation Learning
Gal Mishne, Zhengchao Wan, Yusu Wang et al.
The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation
Philip Amortila, Nan Jiang, Csaba Szepesvari
Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables
Rick Wilming, Leo Kieslich, Benedict Clark et al.
Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming
Yufan Huang, C. Seshadhri, David F. Gleich
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
Hilaf Hasson, Danielle C. Maddix, Bernie Wang et al.
Theory on Forgetting and Generalization of Continual Learning
Sen Lin, Peizhong Ju, Yingbin Liang et al.
The Persistent Laplacian for Data Science: Evaluating Higher-Order Persistent Spectral Representations of Data
Thomas Davies, Zhengchao Wan, Ruben J Sanchez-Garcia
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek et al.
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
Xingyu Xu, Yandi Shen, Yuejie Chi et al.
The Power of Uniform Sampling for k-Median
Lingxiao Huang, Shaofeng H.-C. Jiang, Jianing Lou
The Price of Differential Privacy under Continual Observation
Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar et al.
The Regret of Exploration and the Control of Bad Episodes in Reinforcement Learning
Victor Boone, Bruno Gaujal
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
Borja Rodrı́guez Gálvez, Arno Blaas, Pau Rodriguez et al.
The Saddle-Point Method in Differential Privacy
Wael Alghamdi, Juan Felipe Gomez, Shahab Asoodeh et al.
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
Vivien Cabannes, Bobak Kiani, Randall Balestriero et al.
The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation
Mark Rowland, Yunhao Tang, Clare Lyle et al.