Papers
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
Andrew Foong, David Burt, Yingzhen Li et al.
Few-shot Image Generation with Elastic Weight Consolidation
Yijun Li, Richard Zhang, Jingwan (Cynthia) Lu et al.
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
Hadi Mohaghegh Dolatabadi, Sarah Erfani, Christopher Leckie
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples
Shafi Goldwasser, Adam Tauman Kalai, Yael Kalai et al.
Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity
Shuxiao Chen, Hangfeng He, Weijie Su
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
Tianlong Chen, Jonathan Frankle, Shiyu Chang et al.
Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
Yihan Zhou, Victor Sanches Portella, Mark Schmidt et al.
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs
Hao Tang, Zhiao Huang, Jiayuan Gu et al.
Hitting the High Notes: Subset Selection for Maximizing Expected Order Statistics
Aranyak Mehta, Uri Nadav, Alexandros Psomas et al.
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
Julien Roy, Paul Barde, Félix Harvey et al.
Consequences of Misaligned AI
Simon Zhuang, Dylan Hadfield-Menell
Disentangling Human Error from Ground Truth in Segmentation of Medical Images
Le Zhang, Ryutaro Tanno, Mou-Cheng Xu et al.
Error Bounds of Imitating Policies and Environments
Tian Xu, Ziniu Li, Yang Yu
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
Wei Deng, Guang Lin, Faming Liang
Learning efficient task-dependent representations with synaptic plasticity
Colin Bredenberg, Eero P. Simoncelli, Cristina Savin
Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes
Ayoub El Hanchi, David Stephens
Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing
Arun Jambulapati, Jerry Li, Kevin Tian
The Discrete Gaussian for Differential Privacy
Clément L Canonne, Gautam Kamath, Thomas Steinke
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
Bruno Lecouat, Jean Ponce, Julien Mairal
Neural Sparse Voxel Fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin et al.
Collapsing Bandits and Their Application to Public Health Intervention
Aditya Mate, Jackson Killian, Haifeng Xu et al.
Sparse Weight Activation Training
Md Aamir Raihan, Tor Aamodt
Parametric Instance Classification for Unsupervised Visual Feature learning
Yue Cao, Zhenda Xie, Bin Liu et al.
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Ginevra Carbone, Matthew Wicker, Luca Laurenti et al.