Papers
Positive-Unlabeled Compression on the Cloud
Yixing Xu, Yunhe Wang, Hanting Chen et al.
Post training 4-bit quantization of convolutional networks for rapid-deployment
Ron Banner, Yury Nahshan, Daniel Soudry
Power analysis of knockoff filters for correlated designs
Jingbo Liu, Philippe Rigollet
Powerset Convolutional Neural Networks
Chris Wendler, Markus Püschel, Dan Alistarh
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
Practical and Consistent Estimation of f-Divergences
Paul Rubenstein, Olivier Bousquet, Josip Djolonga et al.
Practical Deep Learning with Bayesian Principles
Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan et al.
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition
David Durfee, Ryan M Rogers
Practical Two-Step Lookahead Bayesian Optimization
Jian Wu, Peter Frazier
Precision-Recall Balanced Topic Modelling
Seppo Virtanen, Mark Girolami
Predicting the Politics of an Image Using Webly Supervised Data
Christopher Thomas, Adriana Kovashka
Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees
Muhammad Osama, Dave Zachariah, Peter Stoica
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models
Farnam Mansouri, Yuxin Chen, Ara Vartanian et al.
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks
Qiyang Li, Saminul Haque, Cem Anil et al.
Primal-Dual Block Generalized Frank-Wolfe
Qi Lei, JIACHENG ZHUO, Constantine Caramanis et al.
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
Yujia Jin, Aaron Sidford
Prior-Free Dynamic Auctions with Low Regret Buyers
Yuan Deng, Jon Schneider, Balasubramanian Sivan
Privacy Amplification by Mixing and Diffusion Mechanisms
Borja Balle, Gilles Barthe, Marco Gaboardi et al.
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation
Devin Reich, Ariel Todoki, Rafael Dowsley et al.
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
Baoxiang Wang, Nidhi Hegde
Private Hypothesis Selection
Mark Bun, Gautam Kamath, Thomas Steinke et al.
Private Learning Implies Online Learning: An Efficient Reduction
Alon Gonen, Elad Hazan, Shay Moran
Private Stochastic Convex Optimization with Optimal Rates
Raef Bassily, Vitaly Feldman, Kunal Talwar et al.
Private Testing of Distributions via Sample Permutations
Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane et al.
PRNet: Self-Supervised Learning for Partial-to-Partial Registration
Yue Wang, Justin M Solomon