Papers
Anytime Online-to-Batch, Optimism and Acceleration
Ashok Cutkosky
A Persistent Weisfeiler-Lehman Procedure for Graph Classification
Bastian Rieck, Christian Bock, Karsten Borgwardt
A Personalized Affective Memory Model for Improving Emotion Recognition
Pablo Barros, German Parisi, Stefan Wermter
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes
Alireza Rezaei, Shayan Oveis Gharan
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
Xiaohan Ding, Guiguang Ding, Yuchen Guo et al.
Approximating Orthogonal Matrices with Effective Givens Factorization
Thomas Frerix, Joan Bruna
Approximation and non-parametric estimation of ResNet-type convolutional neural networks
Kenta Oono, Taiji Suzuki
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent
Yongqiang Cai, Qianxiao Li, Zuowei Shen
Area Attention
Yang Li, Lukasz Kaiser, Samy Bengio et al.
A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
Sylvain Lamprier
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li, John Bradshaw, Yash Sharma
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
Gabriele Abbati, Philippe Wenk, Michael A. Osborne et al.
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
Mingzhang Yin, Yuguang Yue, Mingyuan Zhou
A Statistical Investigation of Long Memory in Language and Music
Alexander Greaves-Tunnell, Zaid Harchaoui
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
Ahsan Alvi, Binxin Ru, Jan-Peter Calliess et al.
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
Umut Simsekli, Levent Sagun, Mert Gurbuzbalaban
A Theoretical Analysis of Contrastive Unsupervised Representation Learning
Nikunj Saunshi, Orestis Plevrakis, Sanjeev Arora et al.
A Theory of Regularized Markov Decision Processes
Matthieu Geist, Bruno Scherrer, Olivier Pietquin
A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes
Jennifer Gillenwater, Alex Kulesza, Zelda Mariet et al.
AUCμ: A Performance Metric for Multi-Class Machine Learning Models
Ross Kleiman, David Page
Automated Model Selection with Bayesian Quadrature
Henry Chai, Jean-Francois Ton, Michael A. Osborne et al.
Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth
Jacob Whitehill, Anand Ramakrishnan
Automatic Posterior Transformation for Likelihood-Free Inference
David Greenberg, Marcel Nonnenmacher, Jakob Macke
Autoregressive Energy Machines
Charlie Nash, Conor Durkan
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
Kaizhi Qian, Yang Zhang, Shiyu Chang et al.