Papers
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
Huaian Diao, Rajesh Jayaram, Zhao Song et al.
Optimal Sparse Decision Trees
Xiyang Hu, Cynthia Rudin, Margo Seltzer
Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation
zengfeng Huang, Ziyue Huang, Yilei WANG et al.
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
Dominic Richards, Patrick Rebeschini
Optimal Stochastic and Online Learning with Individual Iterates
Yunwen Lei, Peng Yang, Ke Tang et al.
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue et al.
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions
Gabriele Farina, Christian Kroer, Tuomas Sandholm
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection
Pan Li, I Chien, Olgica Milenkovic
Optimizing Generalized Rate Metrics with Three Players
Harikrishna Narasimhan, Andrew Cotter, Maya Gupta
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback
Shinji Ito, Daisuke Hatano, Hanna Sumita et al.
Ordered Memory
Yikang Shen, Shawn Tan, Arian Hosseini et al.
Order Optimal One-Shot Distributed Learning
Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani
Ouroboros: On Accelerating Training of Transformer-Based Language Models
Qian Yang, Zhouyuan Huo, Wenlin Wang et al.
Outlier Detection and Robust PCA Using a Convex Measure of Innovation
Mostafa Rahmani, Ping Li
Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber's $M$-estimator
Arnak Dalalyan, Philip Thompson
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
PAC-Bayes under potentially heavy tails
Matthew Holland
PAC-Bayes Un-Expected Bernstein Inequality
Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Sharan Vaswani, Aaron Mishkin, Issam Laradji et al.
Paradoxes in Fair Machine Learning
Paul Goelz, Anson Kahng, Ariel D Procaccia
Parameter elimination in particle Gibbs sampling
Anna Wigren, Riccardo Sven Risuleo, Lawrence Murray et al.
Paraphrase Generation with Latent Bag of Words
Yao Fu, Yansong Feng, John P. Cunningham
Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li et al.
Park: An Open Platform for Learning-Augmented Computer Systems
Hongzi Mao, Parimarjan Negi, Akshay Narayan et al.
Partially Encrypted Deep Learning using Functional Encryption
Théo Ryffel, David Pointcheval, Francis Bach et al.