Papers
Adversarial examples from computational constraints
Sebastien Bubeck, Yin Tat Lee, Eric Price et al.
Adversarial Generation of Time-Frequency Features with application in audio synthesis
Andrés Marafioti, Nathanaël Perraudin, Nicki Holighaus et al.
Adversarially Learned Representations for Information Obfuscation and Inference
Martin Bertran, Natalia Martinez, Afroditi Papadaki et al.
Adversarial Online Learning with noise
Alon Resler, Yishay Mansour
A Dynamical Systems Perspective on Nesterov Acceleration
Michael Muehlebach, Michael Jordan
A Framework for Bayesian Optimization in Embedded Subspaces
Amin Nayebi, Alexander Munteanu, Matthias Poloczek
A fully differentiable beam search decoder
Ronan Collobert, Awni Hannun, Gabriel Synnaeve
Agnostic Federated Learning
Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
Yucheng Chen, Matus Telgarsky, Chao Zhang et al.
A Kernel Perspective for Regularizing Deep Neural Networks
Alberto Bietti, Grégoire Mialon, Dexiong Chen et al.
A Kernel Theory of Modern Data Augmentation
Tri Dao, Albert Gu, Alexander Ratner et al.
A Large-Scale Study on Regularization and Normalization in GANs
Karol Kurach, Mario Lučić, Xiaohua Zhai et al.
Almost surely constrained convex optimization
Olivier Fercoq, Ahmet Alacaoglu, Ion Necoara et al.
Almost Unsupervised Text to Speech and Automatic Speech Recognition
Yi Ren, Xu Tan, Tao Qin et al.
Alternating Minimizations Converge to Second-Order Optimal Solutions
Qiuwei Li, Zhihui Zhu, Gongguo Tang
Amortized Monte Carlo Integration
Adam Golinski, Frank Wood, Tom Rainforth
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology
Onur Dereli, Ceyda Oğuz, Mehmet Gönen
Analogies Explained: Towards Understanding Word Embeddings
Carl Allen, Timothy Hospedales
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst, Nicolas Papernot, Geoffrey Hinton
Analyzing Federated Learning through an Adversarial Lens
Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal et al.
An Instability in Variational Inference for Topic Models
Behrooz Ghorbani, Hamid Javadi, Andrea Montanari
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
Behrooz Ghorbani, Shankar Krishnan, Ying Xiao
An Investigation of Model-Free Planning
Arthur Guez, Mehdi Mirza, Karol Gregor et al.
Anomaly Detection With Multiple-Hypotheses Predictions
Duc Tam Nguyen, Zhongyu Lou, Michael Klar et al.
An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule
Touqir Sajed, Or Sheffet