Papers
On ranking via sorting by estimated expected utility
Clement Calauzenes, Nicolas Usunier
On Regret with Multiple Best Arms
Yinglun Zhu, Robert Nowak
On Reward-Free Reinforcement Learning with Linear Function Approximation
Ruosong Wang, Simon S Du, Lin Yang et al.
On Second Order Behaviour in Augmented Neural ODEs
Alexander Norcliffe, Cristian Bodnar, Ben Day et al.
On Testing of Samplers
Kuldeep S Meel, Yash Pralhad Pote, Sourav Chakraborty
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
Panayotis Mertikopoulos, Nadav Hallak, Ali Kavis et al.
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes
Elena Smirnova, Elvis Dohmatob
On the distance between two neural networks and the stability of learning
Jeremy Bernstein, Arash Vahdat, Yisong Yue et al.
On the Equivalence between Online and Private Learnability beyond Binary Classification
Young Jung, Baekjin Kim, Ambuj Tewari
On the equivalence of molecular graph convolution and molecular wave function with poor basis set
Masashi Tsubaki, Teruyasu Mizoguchi
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method
Ye He, Krishnakumar Balasubramanian, Murat A Erdogdu
On the Error Resistance of Hinge-Loss Minimization
Kunal Talwar
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
Andrew Foong, David Burt, Yingzhen Li et al.
On the linearity of large non-linear models: when and why the tangent kernel is constant
Chaoyue Liu, Libin Zhu, Misha Belkin
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
Chen Liu, Mathieu Salzmann, Tao Lin et al.
On the Modularity of Hypernetworks
Tomer Galanti, Lior Wolf
On the Power of Louvain in the Stochastic Block Model
Vincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn et al.
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Ignavier Ng, AmirEmad Ghassami, Kun Zhang
On the Similarity between the Laplace and Neural Tangent Kernels
Amnon Geifman, Abhay Yadav, Yoni Kasten et al.
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems
Kaiqing Zhang, Bin Hu, Tamer Basar
On the Theory of Transfer Learning: The Importance of Task Diversity
Nilesh Tripuraneni, Michael I. Jordan, Chi Jin
On the Trade-off between Adversarial and Backdoor Robustness
Cheng-Hsin Weng, Yan-Ting Lee, Shan-Hung (Brandon) Wu
On the training dynamics of deep networks with $L_2$ regularization
Aitor Lewkowycz, Guy Gur-Ari