Papers
Coresets for Archetypal Analysis
Sebastian Mair, Ulf Brefeld
Characterizing Bias in Classifiers using Generative Models
Daniel McDuff, Shuang Ma, Yale Song et al.
Approximate Feature Collisions in Neural Nets
Ke Li, Tianhao Zhang, Jitendra Malik
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
Gaël Letarte, Pascal Germain, Benjamin Guedj et al.
Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song, Ruosong Wang, Lin Yang et al.
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
Kevin Liang, Guoyin Wang, Yitong Li et al.
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse
James Lucas, George Tucker, Roger B Grosse et al.
Adversarial Fisher Vectors for Unsupervised Representation Learning
Shuangfei Zhai, Walter Talbott, Carlos Guestrin et al.
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
Andrey Malinin, Mark Gales
Backpropagation-Friendly Eigendecomposition
Wei Wang, Zheng Dang, Yinlin Hu et al.
Direct Estimation of Differential Functional Graphical Models
Boxin Zhao, Y. Samuel Wang, Mladen Kolar
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Roman Beliy, Guy Gaziv, Assaf Hoogi et al.
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Xuechen Li, Yi Wu, Lester Mackey et al.
Learning Hierarchical Priors in VAEs
Alexej Klushyn, Nutan Chen, Richard Kurle et al.
Dancing to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu et al.
Policy Evaluation with Latent Confounders via Optimal Balance
Andrew Bennett, Nathan Kallus
Sparse Variational Inference: Bayesian Coresets from Scratch
Trevor Campbell, Boyan Beronov
Partitioning Structure Learning for Segmented Linear Regression Trees
Xiangyu Zheng, Song Xi Chen
Embedding Symbolic Knowledge into Deep Networks
Yaqi Xie, Ziwei Xu, Mohan S Kankanhalli et al.
Neural Spline Flows
Conor Durkan, Artur Bekasov, Iain Murray et al.
Reconciling meta-learning and continual learning with online mixtures of tasks
Ghassen Jerfel, Erin Grant, Tom Griffiths et al.
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases
Xiyang Liu, Sewoong Oh
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions
Ashia C Wilson, Lester Mackey, Andre Wibisono
Sobolev Independence Criterion
Youssef Mroueh, Tom Sercu, Mattia Rigotti et al.
Structured Prediction with Projection Oracles
Mathieu Blondel