ICLR 2023

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12 Results

Poster		Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms Ximing Li · Chendi Wang · Guang Cheng
Poster		Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions Raghav Singhal · Mark Goldstein · Rajesh Ranganath
Poster		Tensor-Based Sketching Method for the Low-Rank Approximation of Data Streams. Cuiyu Liu · Xiao Chuanfu · Mingshuo Ding · Chao Yang
Poster	Mon 7:30	Diffusion Models for Causal Discovery via Topological Ordering Pedro Sanchez · Xiao Liu · Alison O'Neil · Sotirios Tsaftaris
Oral	Wed 1:20	Solving Constrained Variational Inequalities via a First-order Interior Point-based Method Tong Yang · Michael Jordan · Tatjana Chavdarova
Poster	Wed 2:30	Solving Constrained Variational Inequalities via a First-order Interior Point-based Method Tong Yang · Michael Jordan · Tatjana Chavdarova
Poster	Wed 2:30	Particle-based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong · Xi Wang · LIN Yong · Tong Zhang
Poster	Mon 7:30	Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning Daniel Palenicek · Michael Lutter · Joao Carvalho · Jan Peters
Poster	Wed 2:30	Everybody Needs Good Neighbours: An Unsupervised Locality-based Method for Bias Mitigation Xudong Han · Timothy Baldwin · Trevor Cohn
Poster	Tue 7:30	Energy-Based Test Sample Adaptation for Domain Generalization Zehao Xiao · Xiantong Zhen · Shengcai Liao · Cees G Snoek
Poster		ISAAC Newton: Input-based Approximate Curvature for Newton's Method Felix Petersen · Tobias Sutter · Christian Borgelt · Dongsung Huh · Hilde Kuehne · Yuekai Sun · Oliver Deussen
Poster	Tue 2:30	Sampling-based inference for large linear models, with application to linearised Laplace Javier Antorán · Shreyas Padhy · Riccardo Barbano · Eric Nalisnick · David Janz · José Miguel Hernández Lobato