Papers
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences
Borja Balle, Gilles Barthe, Marco Gaboardi
Probabilistic Matrix Factorization for Automated Machine Learning
Nicolo Fusi, Rishit Sheth, Melih Elibol
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn, Kelvin Xu, Sergey Levine
Probabilistic Neural Programmed Networks for Scene Generation
Zhiwei Deng, Jiacheng Chen, YIFANG FU et al.
(Probably) Concave Graph Matching
Haggai Maron, Yaron Lipman
Processing of missing data by neural networks
Marek Śmieja, Łukasz Struski, Jacek Tabor et al.
Provable Gaussian Embedding with One Observation
Ming Yu, Zhuoran Yang, Tuo Zhao et al.
Provable Variational Inference for Constrained Log-Submodular Models
Josip Djolonga, Stefanie Jegelka, Andreas Krause
Provably Correct Automatic Sub-Differentiation for Qualified Programs
Sham M. Kakade, Jason Lee
Proximal Graphical Event Models
Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao
Proximal SCOPE for Distributed Sparse Learning
Shenyi Zhao, Gong-Duo Zhang, Ming-Wei Li et al.
Q-learning with Nearest Neighbors
Devavrat Shah, Qiaomin Xie
Quadratic Decomposable Submodular Function Minimization
Pan Li, Niao He, Olgica Milenkovic
Quadrature-based features for kernel approximation
Marina Munkhoeva, Yermek Kapushev, Evgeny Burnaev et al.
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
Query K-means Clustering and the Double Dixie Cup Problem
I Chien, Chao Pan, Olgica Milenkovic
Random Feature Stein Discrepancies
Jonathan Huggins, Lester Mackey
Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband, John Aslanides, Albin Cassirer
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Avital Oliver, Augustus Odena, Colin A Raffel et al.
Rectangular Bounding Process
Xuhui Fan, Bin Li, Scott SIsson
Recurrently Controlled Recurrent Networks
Yi Tay, Anh Tuan Luu, Siu Cheung Hui
Recurrent Relational Networks
Rasmus Palm, Ulrich Paquet, Ole Winther
Recurrent Transformer Networks for Semantic Correspondence
Seungryong Kim, Stephen Lin, SANG RYUL JEON et al.
Recurrent World Models Facilitate Policy Evolution
David Ha, Jürgen Schmidhuber