Papers
Probabilistic Boolean Tensor Decomposition
Tammo Rukat, Chris Holmes, Christopher Yau
Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
Luke Vilnis, Xiang Li, Shikhar Murty et al.
Probabilistic FastText for Multi-Sense Word Embeddings
Ben Athiwaratkun, Andrew Wilson, Anima Anandkumar
Probabilistic Joint Face-Skull Modelling for Facial Reconstruction
Dennis Madsen, Marcel Lüthi, Andreas Schneider et al.
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.
Probabilistic Plant Modeling via Multi-View Image-to-Image Translation
Takahiro Isokane, Fumio Okura, Ayaka Ide et al.
Probabilistic preference learning with the Mallows rank model
Valeria Vitelli, Øystein Sørensen, Marta Crispino et al.
Probabilistic Recurrent State-Space Models
Andreas Doerr, Christian Daniel, Martin Schiegg et al.
Probabilistic Verification for Obviously Strategyproof Mechanisms
Diodato Ferraioli, Carmine Ventre
Probability–Revealing Samples
Krzysztof Onak, Xiaorui Sun
Probably Approximately Metric-Fair Learning
Gal Yona, Guy Rothblum
(Probably) Concave Graph Matching
Haggai Maron, Yaron Lipman
Probing sentence embeddings for structure-dependent tense
Geoff Bacon, Terry Regier
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
Andrea Zanette, Emma Brunskill
Processing MWEs: Neurocognitive Bases of Verbal MWEs and Lexical Cohesiveness within MWEs
Shohini Bhattasali, Murielle Fabre, John Hale
Processing of missing data by neural networks
Marek Śmieja, Łukasz Struski, Jacek Tabor et al.
Processing Transition Regions of Glottal Stop Substituted /S/ for Intelligibility Enhancement of Cleft Palate Speech
Protima Nomo Sudro, Sishir Kalita, S R Mahadeva Prasanna
Product Kernel Interpolation for Scalable Gaussian Processes
Jacob Gardner, Geoff Pleiss, Ruihan Wu et al.
Profile-Based Bandit with Unknown Profiles
Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari
Profitable Bandits
Mastane Achab, Stephan Clémençon, Aurélien Garivier
Programmatically Interpretable Reinforcement Learning
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh et al.
Progress & Compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina et al.