Papers
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
Meta Architecture Search
Albert Shaw, Wei Wei, Weiyang Liu et al.
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman Alghunaim, Kun Yuan, Ali H. Sayed
DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging
Matthieu SIMEONI, Sepand Kashani, Paul Hurley et al.
Weight Agnostic Neural Networks
Adam Gaier, David Ha
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
Alexander Mott, Daniel Zoran, Mike Chrzanowski et al.
Deep Model Transferability from Attribution Maps
Jie Song, Yixin Chen, Xinchao Wang et al.