Papers
4,025 papers found
On Feynman-Kac training of partial Bayesian neural networks
Zheng Zhao, Sebastian Mair, Thomas B. Schön et al.
On learning history-based policies for controlling Markov decision processes
Gandharv Patil, Aditya Mahajan, Doina Precup
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou et al.
Online Calibrated and Conformal Prediction Improves Bayesian Optimization
Shachi Deshpande, Charles Marx, Volodymyr Kuleshov
Online Distribution Learning with Local Privacy Constraints
Jin Sima, Changlong Wu, Olgica Milenkovic et al.
Online learning in bandits with predicted context
Yongyi Guo, Ziping Xu, Susan Murphy
Online Learning in Contextual Second-Price Pay-Per-Click Auctions
Mengxiao Zhang, Haipeng Luo
Online Learning of Decision Trees with Thompson Sampling
Ayman Chaouki, Jesse Read, Albert Bifet
Online multiple testing with e-values
Ziyu Xu, Aaditya Ramdas
Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization
Alejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos
On Parameter Estimation in Deviated Gaussian Mixture of Experts
Huy Nguyen, Khai Nguyen, Nhat Ho
On Ranking-based Tests of Independence
Myrto Limnios, Stéphan Clémençon
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Amanda Olmin, Jakob Lindqvist, Lennart Svensson et al.
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective
Yipei Wang, Xiaoqian Wang
On the estimation of persistence intensity functions and linear representations of persistence diagrams
Weichen Wu, Jisu Kim, Alessandro Rinaldo
On the Expected Size of Conformal Prediction Sets
Guneet S. Dhillon, George Deligiannidis, Tom Rainforth
On the Generalization Ability of Unsupervised Pretraining
Yuyang Deng, Junyuan Hong, Jiayu Zhou et al.
On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions
Simon Martin, Francis Bach, Giulio Biroli
On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem
Georg Pichler, Marco Romanelli, Divya Prakash Manivannan et al.
On the Misspecification of Linear Assumptions in Synthetic Controls
Achille O. R. Nazaret, Claudia Shi, David Blei
On the Model-Misspecification in Reinforcement Learning
Yunfan Li, Lin Yang
On the Nyström Approximation for Preconditioning in Kernel Machines
Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher et al.
On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX
Ali Mortazavi, Junhao Lin, Nishant Mehta
On the Privacy of Selection Mechanisms with Gaussian Noise
Jonathan Lebensold, Doina Precup, Borja Balle
On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation
Jiawei Huang, Batuhan Yardim, Niao He