Papers
Thresholding Bandit with Optimal Aggregate Regret
Chao Tao, Saúl Blanco, Jian Peng et al.
Cross-Domain Transferability of Adversarial Perturbations
Muhammad Muzammal Naseer, Salman H Khan, Muhammad Haris Khan et al.
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
Cagatay Yildiz, Markus Heinonen, Harri Lahdesmaki
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
Jonathan Sauder, Bjarne Sievers
The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection
Vladimir V. Kniaz, Vladimir Knyaz, Fabio Remondino
Visual Concept-Metaconcept Learning
Chi Han, Jiayuan Mao, Chuang Gan et al.
Learning Nearest Neighbor Graphs from Noisy Distance Samples
Blake Mason, Ardhendu Tripathy, Robert Nowak
Neural Temporal-Difference Learning Converges to Global Optima
Qi Cai, Zhuoran Yang, Jason Lee et al.
Block Coordinate Regularization by Denoising
Yu Sun, Jiaming Liu, Ulugbek Kamilov
Object landmark discovery through unsupervised adaptation
Enrique Sanchez, Georgios Tzimiropoulos
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Andrei Barbu, David Mayo, Julian Alverio et al.
Private Hypothesis Selection
Mark Bun, Gautam Kamath, Thomas Steinke et al.
Deep ReLU Networks Have Surprisingly Few Activation Patterns
Boris Hanin, David Rolnick
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
Rixon Crane, Fred Roosta
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes
Jun Yang, Shengyang Sun, Daniel M. Roy
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
Zhuoran Yang, Yongxin Chen, Mingyi Hong et al.
Distributional Reward Decomposition for Reinforcement Learning
Zichuan Lin, Li Zhao, Derek Yang et al.
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes
Rishidev Chaudhuri, Ila Fiete
Kernelized Bayesian Softmax for Text Generation
Ning Miao, Hao Zhou, Chengqi Zhao et al.
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation
Samuel Ainsworth, Matt Barnes, Siddhartha Srinivasa
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Mahyar Fazlyab, Alexander Robey, Hamed Hassani et al.
Learning Compositional Neural Programs with Recursive Tree Search and Planning
Thomas PIERROT, Guillaume Ligner, Scott E Reed et al.
Learning Deep Bilinear Transformation for Fine-grained Image Representation
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha et al.
Adaptive Density Estimation for Generative Models
Thomas Lucas, Konstantin Shmelkov, Karteek Alahari et al.