Papers
Outlier-robust estimation of a sparse linear model using ℓ_1-penalized Huber's M-estimator
Arnak Dalalyan, Philip Thompson
Generalized Sliced Wasserstein Distances
Soheil Kolouri, Kimia Nadjahi, Umut Simsekli et al.
Differentially Private Anonymized Histograms
Ananda Theertha Suresh
Deep Scale-spaces: Equivariance Over Scale
Daniel Worrall, Max Welling
Abstract Reasoning with Distracting Features
Kecheng Zheng, Zheng-Jun Zha, Wei Wei
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan et al.
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
Peng Chen, Keyi Wu, Joshua Chen et al.
A Meta-Analysis of Overfitting in Machine Learning
Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht et al.
STREETS: A Novel Camera Network Dataset for Traffic Flow
Corey Snyder, Minh Do
Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees
Muhammad Osama, Dave Zachariah, Peter Stoica
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
Chao Yang, Xiaojian Ma, Wenbing Huang et al.
Statistical Model Aggregation via Parameter Matching
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh et al.
A Little Is Enough: Circumventing Defenses For Distributed Learning
Gilad Baruch, Moran Baruch, Yoav Goldberg
Learning to Optimize in Swarms
Yue Cao, Tianlong Chen, Zhangyang Wang et al.
Adversarial Music: Real world Audio Adversary against Wake-word Detection System
Juncheng Li, Shuhui Qu, Xinjian Li et al.
PRNet: Self-Supervised Learning for Partial-to-Partial Registration
Yue Wang, Justin M Solomon
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning
Harm Van Seijen, Mehdi Fatemi, Arash Tavakoli
Face Reconstruction from Voice using Generative Adversarial Networks
Yandong Wen, Bhiksha Raj, Rita Singh
The Randomized Midpoint Method for Log-Concave Sampling
Ruoqi Shen, Yin Tat Lee
PIDForest: Anomaly Detection via Partial Identification
Parikshit Gopalan, Vatsal Sharan, Udi Wieder
Transfusion: Understanding Transfer Learning for Medical Imaging
Maithra Raghu, Chiyuan Zhang, Jon Kleinberg et al.
A Primal-Dual link between GANs and Autoencoders
Hisham Husain, Richard Nock, Robert C. Williamson
Universal Invariant and Equivariant Graph Neural Networks
Nicolas Keriven, Gabriel Peyré
Graph Structured Prediction Energy Networks
Colin Graber, Alexander Schwing
Double Quantization for Communication-Efficient Distributed Optimization
Yue Yu, Jiaxiang Wu, Longbo Huang