Papers
Combinatorial Bandits with Relative Feedback
Aadirupa Saha, Aditya Gopalan
Paraphrase Generation with Latent Bag of Words
Yao Fu, Yansong Feng, John P. Cunningham
Abstraction based Output Range Analysis for Neural Networks
Pavithra Prabhakar, Zahra Rahimi Afzal
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate
James Jordon, Jinsung Yoon, Mihaela van der Schaar
Stein Variational Gradient Descent With Matrix-Valued Kernels
Dilin Wang, Ziyang Tang, Chandrajit Bajaj et al.
Certainty Equivalence is Efficient for Linear Quadratic Control
Horia Mania, Stephen Tu, Benjamin Recht
Adversarial Training and Robustness for Multiple Perturbations
Florian Tramer, Dan Boneh
Copula Multi-label Learning
Weiwei Liu
Residual Flows for Invertible Generative Modeling
Ricky T. Q. Chen, Jens Behrmann, David K. Duvenaud et al.
Implicit Regularization for Optimal Sparse Recovery
Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
Xuanqing Liu, Si Si, Xiaojin Zhu et al.
Large Scale Markov Decision Processes with Changing Rewards
Adrian Rivera Cardoso, He Wang, Huan Xu
Transductive Zero-Shot Learning with Visual Structure Constraint
Ziyu Wan, Dongdong Chen, Yan Li et al.
Minimal Variance Sampling in Stochastic Gradient Boosting
Bulat Ibragimov, Gleb Gusev
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine
Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation
zengfeng Huang, Ziyue Huang, Yilei WANG et al.
Variational Bayesian Decision-making for Continuous Utilities
Tomasz Kuśmierczyk, Joseph Sakaya, Arto Klami
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
Creighton Heaukulani, Mark van der Wilk
A Game Theoretic Approach to Class-wise Selective Rationalization
Shiyu Chang, Yang Zhang, Mo Yu et al.
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
Gonzalo Mena, Jonathan Niles-Weed
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Basri Ronen, David Jacobs, Yoni Kasten et al.
Imitation-Projected Programmatic Reinforcement Learning
Abhinav Verma, Hoang Le, Yisong Yue et al.
Explicitly disentangling image content from translation and rotation with spatial-VAE
Tristan Bepler, Ellen Zhong, Kotaro Kelley et al.
Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization
Miika Aittala, Prafull Sharma, Lukas Murmann et al.
Multi-mapping Image-to-Image Translation via Learning Disentanglement
Xiaoming Yu, Yuanqi Chen, Shan Liu et al.