Papers
Identifying Causal Effects via Context-specific Independence Relations
Santtu Tikka, Antti Hyttinen, Juha Karvanen
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang, Jianyu Wang
Cross-channel Communication Networks
Jianwei Yang, Zhile Ren, Chuang Gan et al.
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner, Michael Schmidt, Heinz Koeppl
Unsupervised learning of object structure and dynamics from videos
Matthias Minderer, Chen Sun, Ruben Villegas et al.
GNNExplainer: Generating Explanations for Graph Neural Networks
Zhitao Ying, Dylan Bourgeois, Jiaxuan You et al.
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
Axel Brando, Jose A Rodriguez, Jordi Vitria et al.
Adaptive Cross-Modal Few-shot Learning
Chen Xing, Negar Rostamzadeh, Boris Oreshkin et al.
LCA: Loss Change Allocation for Neural Network Training
Janice Lan, Rosanne Liu, Hattie Zhou et al.
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover, Jiaming Song, Ashish Kapoor et al.
Offline Contextual Bandits with High Probability Fairness Guarantees
Blossom Metevier, Stephen Giguere, Sarah Brockman et al.
Ask not what AI can do, but what AI should do: Towards a framework of task delegability
Brian Lubars, Chenhao Tan
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban et al.
Thinning for Accelerating the Learning of Point Processes
Tianbo Li, Yiping Ke
Recurrent Kernel Networks
Dexiong Chen, Laurent Jacob, Julien Mairal
Doubly-Robust Lasso Bandit
Gi-Soo Kim, Myunghee Cho Paik
Improved Regret Bounds for Bandit Combinatorial Optimization
Shinji Ito, Daisuke Hatano, Hanna Sumita et al.
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri, Kyle Hsu, Abhishek Gupta et al.
Neural Machine Translation with Soft Prototype
Yiren Wang, Yingce Xia, Fei Tian et al.
Flexible Modeling of Diversity with Strongly Log-Concave Distributions
Joshua Robinson, Suvrit Sra, Stefanie Jegelka
Variational Bayesian Optimal Experimental Design
Adam Foster, Martin Jankowiak, Elias Bingham et al.
Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution
Thang Vu, Hyunjun Jang, Trung X. Pham et al.
Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds
Nathan Kallus, Angela Zhou