Papers
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
A Swiss Army Knife for Minimax Optimal Transport
Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff et al.
Asynchronous Coagent Networks
James Kostas, Chris Nota, Philip Thomas
A Tree-Structured Decoder for Image-to-Markup Generation
Jianshu Zhang, Jun Du, Yongxin Yang et al.
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang, Xilie Xu, Bo Han et al.
Attentive Group Equivariant Convolutional Networks
David Romero, Erik Bekkers, Jakub Tomczak et al.
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri et al.
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
Yonggan Fu, Wuyang Chen, Haotao Wang et al.
Automated Synthetic-to-Real Generalization
Wuyang Chen, Zhiding Yu, Zhangyang Wang et al.
Automatic Reparameterisation of Probabilistic Programs
Maria Gorinova, Dave Moore, Matthew Hoffman
Automatic Shortcut Removal for Self-Supervised Representation Learning
Matthias Minderer, Olivier Bachem, Neil Houlsby et al.
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real, Chen Liang, David So et al.
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf, Max Simchowitz, Sarah Dean et al.
Bandits for BMO Functions
Tianyu Wang, Cynthia Rudin
Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme
Batch Reinforcement Learning with Hyperparameter Gradients
Byungjun Lee, Jongmin Lee, Peter Vrancx et al.
Batch Stationary Distribution Estimation
Junfeng Wen, Bo Dai, Lihong Li et al.
Bayesian Differential Privacy for Machine Learning
Aleksei Triastcyn, Boi Faltings
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
Steven Kleinegesse, Michael U. Gutmann
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki et al.
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
Csaba Toth, Harald Oberhauser
Bayesian Optimisation over Multiple Continuous and Categorical Inputs
Binxin Ru, Ahsan Alvi, Vu Nguyen et al.
Bayesian Sparsification of Deep C-valued Networks
Ivan Nazarov, Evgeny Burnaev
Being Bayesian about Categorical Probability
Taejong Joo, Uijung Chung, Min-Gwan Seo
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Agustinus Kristiadi, Matthias Hein, Philipp Hennig