Papers
A Spectral Perspective of DNN Robustness to Label Noise
Oshrat Bar, Amnon Drory, Raja Giryes
Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches
Hao Wu, Anthony Wirth
Asynchronous Distributed Optimization with Stochastic Delays
Margalit R. Glasgow, Mary Wootters
Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
Chuanhao Li, Hongning Wang
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming
Robin A. Brown, Edward Schmerling, Navid Azizan et al.
A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
Kevin Bello, Chuyang Ke, Jean Honorio
A Witness Two-Sample Test
Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf et al.
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
Xun Qian, Rustem Islamov, Mher Safaryan et al.
Bayesian Classifier Fusion with an Explicit Model of Correlation
Susanne Trick, Constantin Rothkopf
Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved Confounding
Jiajing Zheng, Alexander D’Amour, Alexander Franks
Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes
Felix Opolka, Pietro Lió
Being a Bit Frequentist Improves Bayesian Neural Networks
Agustinus Kristiadi, Matthias Hein, Philipp Hennig
Best Arm Identification with Safety Constraints
Zhenlin Wang, Andrew J. Wagenmaker, Kevin Jamieson
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
Yongchan Kwon, James Zou
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge
Arshdeep Sekhon, Zhe Wang, Yanjun Qi
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
Romain Laroche, Remi Tachet Des Combes
Bias-Variance Decompositions for Margin Losses
Danny Wood, Tingting Mu, Gavin Brown
Calibration Error for Heterogeneous Treatment Effects
Yizhe Xu, Steve Yadlowsky
Can Functional Transfer Methods Capture Simple Inductive Biases?
Arne Nix, Suhas Shrinivasan, Edgar Y. Walker et al.
Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical Analysis
Jiaye Teng, Weiran Huang, Haowei He
Can we Generalize and Distribute Private Representation Learning?
Sheikh Shams Azam, Taejin Kim, Seyyedali Hosseinalipour et al.
CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric Models
Yirui Liu, Xinghao Qiao, Jessica Lam
Causal Effect Identification with Context-specific Independence Relations of Control Variables
Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami et al.
Causally motivated shortcut removal using auxiliary labels
Maggie Makar, Ben Packer, Dan Moldovan et al.
Certifiably Robust Variational Autoencoders
Ben Barrett, Alexander Camuto, Matthew Willetts et al.