Papers
Probabilistic Logic Neural Networks for Reasoning
Meng Qu, Jian Tang
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning
Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Robert Kleinberg, Kevin Leyton-Brown, Brendan Lucier et al.
Program Synthesis and Semantic Parsing with Learned Code Idioms
Eui Chul Shin, Miltiadis Allamanis, Marc Brockschmidt et al.
Progressive Augmentation of GANs
Dan Zhang, Anna Khoreva
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
Peng Chen, Keyi Wu, Joshua Chen et al.
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
Alberto Maria Metelli, Amarildo Likmeta, Marcello Restelli
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes
Matt Jordan, Justin Lewis, Alexandros G Dimakis
Provable Non-linear Inductive Matrix Completion
Kai Zhong, Zhao Song, Prateek Jain et al.
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
Simon S Du, Yuping Luo, Ruosong Wang et al.
Provably Efficient Q-Learning with Low Switching Cost
Yu Bai, Tengyang Xie, Nan Jiang et al.
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
Zhuoran Yang, Yongxin Chen, Mingyi Hong et al.
Provably Powerful Graph Networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky et al.
Provably robust boosted decision stumps and trees against adversarial attacks
Maksym Andriushchenko, Matthias Hein
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman, Jerry Li, Ilya Razenshteyn et al.
Pseudo-Extended Markov chain Monte Carlo
Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone et al.
Pure Exploration with Multiple Correct Answers
Rémy Degenne, Wouter M. Koolen
Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently
Xiao Liu, Xiaolong Zou, Zilong Ji et al.
Putting An End to End-to-End: Gradient-Isolated Learning of Representations
Sindy Löwe, Peter O'Connor, Bastiaan Veeling
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa et al.
q-means: A quantum algorithm for unsupervised machine learning
Iordanis Kerenidis, Jonas Landman, Alessandro Luongo et al.
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
Debraj Basu, Deepesh Data, Can Karakus et al.
Quadratic Video Interpolation
Xiangyu Xu, Li Siyao, Wenxiu Sun et al.
Quality Aware Generative Adversarial Networks
KANCHARLA PARIMALA, Sumohana Channappayya