Papers
BoFire: Bayesian Optimization Framework Intended for Real Experiments
Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte et al.
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection
Chengde Qian, Guanghui Wang, Changliang Zou
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
Charles C. Margossian, Loucas Pillaud-Vivien, Lawrence K. Saul
Are Ensembles Getting Better All the Time?
Pierre-Alexandre Mattei, Damien Garreau
An Adaptive Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition
Qihang Lin, Negar Soheili, Runchao Ma et al.
Operator Learning for Hyperbolic PDEs
Christopher Wang, Alex Townsend
Optimal subsampling for high-dimensional partially linear models via machine learning methods
Yujing Shao, Lei Wang, Heng Lian et al.
Decentralized Sparse Linear Regression via Gradient-Tracking
Marie Maros, Gesualdo Scutari, Ying Sun et al.
Calibrated Inference: Statistical Inference that Accounts for Both Sampling Uncertainty and Distributional Uncertainty
Yujin Jeong, Dominik Rothenhäusler
Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization
Sébastien J. Petit, Julien Bect, Emmanuel Vazquez
On the Convergence of Projected Policy Gradient for Any Constant Step Sizes
Jiacai Liu, Wenye Li, Dachao Lin et al.
Learning with Linear Function Approximations in Mean-Field Control
Erhan Bayraktar, Ali Devran Kara
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization
Junwen Qiu, Xiao Li, Andre Milzarek
Model-free Change-Point Detection Using AUC of a Classifier
Rohit Kanrar, Feiyu Jiang, Zhanrui Cai
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback
Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov et al.
Multiple Instance Verification
Xin Xu, Eibe Frank, Geoffrey Holmes
Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
Ye Tian, Yuqi Gu, Yang Feng
Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data
Yanxin Jin, Yang Ning, Kean Ming Tan
Optimizing Return Distributions with Distributional Dynamic Programming
Bernardo Ávila Pires, Mark Rowland, Diana Borsa et al.
Early Alignment in Two-Layer Networks Training is a Two-Edged Sword
Etienne Boursier, Nicolas Flammarion
Hierarchical Decision Making Based on Structural Information Principles
Xianghua Zeng, Hao Peng, Dingli Su et al.
Generative Adversarial Networks: Dynamics
Matias G. Delgadino, Bruno B. Suassuna, Rene Cabrera
"What is Different Between These Datasets?" A Framework for Explaining Data Distribution Shifts
Varun Babbar*, Zhicheng Guo*, Cynthia Rudin