Papers
Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression
Pratik Patil, Yuting Wei, Alessandro Rinaldo et al.
Unifying Clustered and Non-stationary Bandits
Chuanhao Li, Qingyun Wu, Hongning Wang
Variational Autoencoder with Learned Latent Structure
Marissa Connor, Gregory Canal, Christopher Rozell
Variational inference for nonlinear ordinary differential equations
Sanmitra Ghosh, Paul Birrell, Daniela De Angelis
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong, Hossein Hajimirsadeghi, Jiawei He et al.
vqSGD: Vector Quantized Stochastic Gradient Descent
Venkata Gandikota, Daniel Kane, Raj Kumar Maity et al.
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
Qiming Du, Gérard Biau, Francois Petit et al.
When MAML Can Adapt Fast and How to Assist When It Cannot
Sébastien Arnold, Shariq Iqbal, Fei Sha
When OT meets MoM: Robust estimation of Wasserstein Distance
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi et al.
When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
Ziwei Guan, Tengyu Xu, Yingbin Liang
Why did the distribution change?
Kailash Budhathoki, Dominik Janzing, Patrick Bloebaum et al.
Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information
Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi
γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator
Masahiro Fujisawa, Takeshi Teshima, Issei Sato et al.
Accelerated Bayesian Optimisation through Weight-Prior Tuning
Alistair Shilton, Sunil Gupta, Santu Rana et al.
Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization
Dongruo Zhou, Yuan Cao, Quanquan Gu
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
Jinming Xu, Ye Tian, Ying Sun et al.
Accelerating Gradient Boosting Machines
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva et al.
Accelerating Smooth Games by Manipulating Spectral Shapes
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas et al.
A Characterization of Mean Squared Error for Estimator with Bagging
Martin Mihelich, Charles Dognin, Yan Shu et al.
A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization
Foivos Alimisis, Antonio Orvieto, Gary Becigneul et al.
Active Community Detection with Maximal Expected Model Change
Dan Kushnir, Benjamin Mirabelli
Adaptive Discretization for Evaluation of Probabilistic Cost Functions
Christoph Zimmer, Danny Driess, Mona Meister et al.
Adaptive, Distribution-Free Prediction Intervals for Deep Networks
Danijel Kivaranovic, Kory D. Johnson, Hannes Leeb
Adaptive Exploration in Linear Contextual Bandit
Botao Hao, Tor Lattimore, Csaba Szepesvari