Papers
Parametric Simplex Method for Sparse Learning
Haotian Pang, Han Liu, Robert J Vanderbei et al.
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins, Ryan P. Adams, Tamara Broderick
Permutation-based Causal Inference Algorithms with Interventions
Yuhao Wang, Liam Solus, Karren Yang et al.
Perturbative Black Box Variational Inference
Robert Bamler, Cheng Zhang, Manfred Opper et al.
Phase Transitions in the Pooled Data Problem
Jonathan Scarlett, Volkan Cevher
PixelGAN Autoencoders
Alireza Makhzani, Brendan J. Frey
Pixels to Graphs by Associative Embedding
Alejandro Newell, Jia Deng
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Caglar Gulcehre, Francis Dutil, Adam Trischler et al.
Poincaré Embeddings for Learning Hierarchical Representations
Maximillian Nickel, Douwe Kiela
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles Ruizhongtai Qi, Li Yi, Hao Su et al.
Policy Gradient With Value Function Approximation For Collective Multiagent Planning
Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication
Qian Yu, Mohammad Maddah-Ali, Salman Avestimehr
Polynomial time algorithms for dual volume sampling
Chengtao Li, Stefanie Jegelka, Suvrit Sra
Population Matching Discrepancy and Applications in Deep Learning
Jianfei Chen, Chongxuan LI, Yizhong Ru et al.
Pose Guided Person Image Generation
Liqian Ma, Xu Jia, Qianru Sun et al.
Position-based Multiple-play Bandit Problem with Unknown Position Bias
Junpei Komiyama, Junya Honda, Akiko Takeda
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo, Gang Niu, Marthinus C du Plessis et al.
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi, Wei Ji Ma
Practical Data-Dependent Metric Compression with Provable Guarantees
Piotr Indyk, Ilya Razenshteyn, Tal Wagner
Practical Hash Functions for Similarity Estimation and Dimensionality Reduction
Søren Dahlgaard, Mathias Knudsen, Mikkel Thorup
Practical Locally Private Heavy Hitters
Raef Bassily, Kobbi Nissim, Uri Stemmer et al.
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
Wengong Jin, Connor Coley, Regina Barzilay et al.
Predicting Scene Parsing and Motion Dynamics in the Future
Xiaojie Jin, Huaxin Xiao, Xiaohui Shen et al.
Predicting User Activity Level In Point Processes With Mass Transport Equation
Yichen Wang, Xiaojing Ye, Hongyuan Zha et al.