UAI 2022

230 papers

Causal inference with treatment measurement error: a nonparametric instrumental variable approach

Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva

Information design for multiple independent and self-interested defenders: Work less, pay off more

Chenghan Zhou, Andrew Spivey, Haifeng Xu, Thanh Hong Nguyen

Convergence Analysis of Linear Coupling with Inexact Proximal Operator

Qiang Zhou, Sinno Jialin Pan

Causal discovery with heterogeneous observational data

Fangting Zhou, Kejun He, Yang Ni

Research on video adversarial attack with long living cycle

Zeyu Zhao, Ke Xu, Xinghao Jiang, Tanfeng Sun

Stability of SGD: Tightness analysis and improved bounds

Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen

Distributed adversarial training to robustify deep neural networks at scale

Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen

Asymptotic optimality for active learning processes

Xueying Zhan, Yaowei Wang, Antoni B. Chan

Principle of relevant information for graph sparsification

Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe

Predictive Whittle networks for time series

Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt

Learning binary multi-scale games on networks

Sixie Yu, P. Jeffrey Brantingham, Matthew Valasik, Yevgeniy Vorobeychik

Cross-domain adaptive transfer reinforcement learning based on state-action correspondence

Heng You, Tianpei Yang, YAN ZHENG, Jianye Hao, E. Taylor Matthew

Active learning with label comparisons

Gal Yona, Shay Moran, Gal Elidan, Amir Globerson

Offline stochastic shortest path: Learning, evaluation and towards optimality

Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang

Superposing many tickets into one: A performance booster for sparse neural network training

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems

Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du

Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set

Mao Ye, Qiang Liu

Noisy L0-sparse subspace clustering on dimensionality reduced data

Yingzhen Yang, Ping Li

CoSPA: An improved masked language model with copy mechanism for Chinese spelling correction

Shoujian Yang, Lian Yu

Robust textual embedding against word-level adversarial attacks

Yichen Yang, Xiaosen Wang, Kun He

Self-supervised representations for multi-view reinforcement learning

Huanhuan Yang, Dianxi Shi, Guojun Xie, Yingxuan Peng, Yi Zhang

Differentially private SGDA for minimax problems

ZHENHUAN YANG, Shu Hu, Yunwen Lei, Kush R Vashney, Siwei Lyu

Addressing token uniformity in transformers via singular value transformation

Hanqi Yan, Lin Gui, Wenjie Li, Yulan He

Finite-horizon equilibria for neuro-symbolic concurrent stochastic games

Rui Yan, Gabriel Santos, Xiaoming Duan, David Parker, Marta Kwiatkowska

Deterministic policy gradient: Convergence analysis

Huaqing. Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang

Fine-Grained matching with multi-perspective similarity modeling for cross-modal retrieval

Xiumin Xie, Chuanwen Hou, Zhixin Li

Partial likelihood Thompson sampling

Han Wu, Stefan Wager

Differentially private multi-party data release for linear regression

Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu

Residual bootstrap exploration for stochastic linear bandit

Shuang Wu, Chi-Hua Wang, Yuantong Li, Guang Cheng

A new constructive criterion for Markov equivalence of MAGs

Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz

Causal discovery under a confounder blanket

David S. Watson, Ricardo Silva

Generalized Bayesian quadrature with spectral kernels

Houston Warren, Rafael Oliveira, Fabio Ramos

Toward learning human-aligned cross-domain robust models by countering misaligned features

Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing

ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning

Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi

Detecting textual adversarial examples through randomized substitution and vote

Xiaosen Wang, Xiong Yifeng, Kun He

Meta-learning without data via Wasserstein distributionally-robust model fusion

Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song

Bias aware probabilistic Boolean matrix factorization

Changlin Wan, Pengtao Dang, Tong Zhao, Yong Zang, Chi Zhang

Bayesian federated estimation of causal effects from observational data

Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong

Intervention target estimation in the presence of latent variables

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Causal forecasting: generalization bounds for autoregressive models

Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar

Learning invariant weights in neural networks

Tycho F.A. van der Ouderaa, Mark van der Wilk

Towards unsupervised open world semantic segmentation

Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk

Multi-source domain adaptation via weighted joint distributions optimal transport

Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil

Learning linear non-Gaussian polytree models

Daniele Tramontano, Anthea Monod, Mathias Drton

Efficient inference for dynamic topic modeling with large vocabularies

Federico Tomasi, Mounia Lalmas, Zhenwen Dai

Semi-supervised novelty detection using ensembles with regularized disagreement

Alexandru Tifrea, Eric Stavarache, Fanny Yang

Contrastive latent variable models for neural text generation

Zhiyang Teng, Chenhua Chen, Yan Zhang, Yue Zhang

High-probability bounds for robust stochastic Frank-Wolfe algorithm

Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee

Marginal MAP estimation for inverse RL under occlusion with observer noise

Prasanth Sengadu Suresh, Prashant Doshi

Simplified and unified analysis of various learning problems by reduction to Multiple-Instance Learning

Daiki Suehiro, Eiji Takimoto

A robustness test for estimating total effects with covariate adjustment

Zehao Su, Leonard Henckel

SMT-based weighted model integration with structure awareness

Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani

Mutual information based Bayesian graph neural network for few-shot learning

Kaiyu Song, Kun Yue, Liang Duan, Mingze Yang, Angsheng Li

Fast inference and transfer of compositional task structures for few-shot task generalization

Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur

Enhanced adaptive optics control with image to image translation

Jeffrey Smith, Jesse Cranney, Charles Gretton, Damien Gratadour

VQ-Flows: Vector quantized local normalizing flows

Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu Balan, Maneesh K. Singh

PAC-Bayesian domain adaptation bounds for multiclass learners

Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang

Shifted compression framework: generalizations and improvements

Egor Shulgin, Peter Richtarik

Neural ensemble search via Bayesian sampling

YAO SHU, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low

Conditional simulation using diffusion Schrödinger bridges

Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet

Reframed GES with a neural conditional dependence measure

Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen

SymNet 2.0: Effectively handling Non-Fluents and Actions in Generalized Neural Policies for RDDL Relational MDPs

Vishal Sharma, Daman Arora, Florian Geißer, Mausam, Parag Singla

Learning functions on multiple sets using multi-set transformers

Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart

Probabilistic spatial transformer networks

Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg

How unfair is private learning?

Amartya Sanyal, Yaxi Hu, Fanny Yang

Robust identifiability in linear structural equation models of causal inference

Karthik A. Sankararaman, Anand Louis, Navin Goyal

Feature learning and random features in standard finite-width convolutional neural networks: An empirical study

Maxim Samarin, Volker Roth, David Belius

Resolving label uncertainty with implicit posterior models

Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson

Quantum perceptron revisited: Computational-statistical tradeoffs

Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri

A free lunch from the noise: Provable and practical exploration for representation learning

Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai

Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently

Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth

Learning in Markov games: Can we exploit a general-sum opponent?

Giorgia Ramponi, Marcello Restelli

Clustering a union of linear subspaces via matrix factorization and innovation search

Mostafa Rahmani

Voronoi density estimator for high-dimensional data: Computation, compactification and convergence

Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny

Using hierarchies to efficiently combine evidence with Dempster’s rule of combination

Daira Pinto Prieto, Ronald de Haan

Bayesian quantile and expectile optimisation

Victor Picheny, Henry Moss, Léonard Torossian, Nicolas Durrande

Identifiability of sparse causal effects using instrumental variables

Niklas Pfister, Jonas Peters

AND/OR branch-and-bound for computational protein design optimizing K*

Bobak Pezeshki, Radu Marinescu, Alexander Ihler, Rina Dechter

Learning large Bayesian networks with expert constraints

Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider

Attribution of predictive uncertainties in classification models

Iker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton

Robust learning of tractable probabilistic models

Rohith Peddi, Tahrima Rahman, Vibhav Gogate

Understanding and mitigating the limitations of prioritized experience replay

Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao

Evaluating high-order predictive distributions in deep learning

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu

An explore-then-commit algorithm for submodular maximization under full-bandit feedback

Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn

Ordinal causal discovery

Yang Ni, Bani Mallick

Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation

Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran

Efficient and accurate top-k recovery from choice data

Duc Nguyen

Robust Bayesian recourse

Tuan-Duy H. Nguyen, Ngoc Bui, Duy Nguyen, Man-Chung Yue, Viet Anh Nguyen

CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs

Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu, Abhishek Gupta

Linearizing contextual bandits with latent state dynamics

Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf

Efficient learning of sparse and decomposable PDEs using random projection

Md Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue

Partially adaptive regularized multiple regression analysis for estimating linear causal effects

Hisayoshi Nanmo, manabu kuroki

Semiparametric causal sufficient dimension reduction of multidimensional treatments

Razieh Nabi, Todd McNutt, Ilya Shpitser

Data augmentation in Bayesian neural networks and the cold posterior effect

Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk

Probabilistic surrogate networks for simulators with unbounded randomness

Andreas Munk, Berend Zwartsenberg, Adam Scibior, Atılım Güneş G. Baydin, Andrew Stewart

ReVar: Strengthening policy evaluation via reduced variance sampling

Subhojyoti Mukherjee, Josiah P. Hanna, Robert D Nowak

Safety aware changepoint detection for piecewise i.i.d. bandits

Subhojyoti Mukherjee

Set-valued prediction in hierarchical classification with constrained representation complexity

Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman

Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classification

Joao Monteiro, Mohamed Osama Ahmed, Hoseein Hajimirsadeghi, Greg Mori

Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction?

Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri