Papers
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu, Heiko Zimmermann, Eli Sennesh et al.
An Accelerated DFO Algorithm for Finite-sum Convex Functions
Yuwen Chen, Antonio Orvieto, Aurelien Lucchi
A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
Ramin Hasani, Mathias Lechner, Alexander Amini et al.
Anderson Acceleration of Proximal Gradient Methods
Vien Mai, Mikael Johansson
A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model
Peng Wang, Zirui Zhou, Anthony Man-Cho So
An EM Approach to Non-autoregressive Conditional Sequence Generation
Zhiqing Sun, Yiming Yang
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam et al.
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
Chris Decarolis, Mukul Ram, Seyed Esmaeili et al.
A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos et al.
An Explicitly Relational Neural Network Architecture
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell et al.
Angular Visual Hardness
Beidi Chen, Weiyang Liu, Zhiding Yu et al.
An Imitation Learning Approach for Cache Replacement
Evan Liu, Milad Hashemi, Kevin Swersky et al.
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh et al.
An Optimistic Perspective on Offline Reinforcement Learning
Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi
A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Brian Brubach, Darshan Chakrabarti, John Dickerson et al.
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
Javier Turek, Shailee Jain, Vy Vo et al.
Approximation Capabilities of Neural ODEs and Invertible Residual Networks
Han Zhang, Xi Gao, Jacob Unterman et al.
A Quantile-based Approach for Hyperparameter Transfer Learning
David Salinas, Huibin Shen, Valerio Perrone
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
Jae Hyun Lim, Aaron Courville, Christopher Pal et al.
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Mikhail Khodak et al.
A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition
Anurag Kumar, Vamsi Ithapu
A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi et al.
A simpler approach to accelerated optimization: iterative averaging meets optimism
Pooria Joulani, Anant Raj, Andras Gyorgy et al.