Papers
Optimal Testing for Properties of Distributions
Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference
Ted Meeds, Max Welling
Orthogonal NMF through Subspace Exploration
Megasthenis Asteris, Dimitris Papailiopoulos, Alexandros G Dimakis
Parallel Correlation Clustering on Big Graphs
Xinghao Pan, Dimitris Papailiopoulos, Samet Oymak et al.
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang, Fangjian Guo, Katherine A. Heller et al.
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
Marijn F Stollenga, Wonmin Byeon, Marcus Liwicki et al.
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah, Zoubin Ghahramani
Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models
Akihiro Kishimoto, Radu Marinescu, Adi Botea
Particle Gibbs for Infinite Hidden Markov Models
Nilesh Tripuraneni, Shixiang (Shane) Gu, Hong Ge et al.
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Behnam Neyshabur, Ruslan Salakhutdinov, Nati Srebro
Planar Ultrametrics for Image Segmentation
Julian E Yarkony, Charless Fowlkes
Pointer Networks
Oriol Vinyals, Meire Fortunato, Navdeep Jaitly
Policy Evaluation Using the Ω-Return
Philip S. Thomas, Scott Niekum, Georgios Theocharous et al.
Policy Gradient for Coherent Risk Measures
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh et al.
Practical and Optimal LSH for Angular Distance
Alexandr Andoni, Piotr Indyk, Thijs Laarhoven et al.
Precision-Recall-Gain Curves: PR Analysis Done Right
Peter Flach, Meelis Kull
Preconditioned Spectral Descent for Deep Learning
David E Carlson, Edo Collins, Ya-Ping Hsieh et al.
Predtron: A Family of Online Algorithms for General Prediction Problems
Prateek Jain, Nagarajan Natarajan, Ambuj Tewari
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Jonas W Mueller, Tommi Jaakkola
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
Vivien Seguy, Marco Cuturi
Private Graphon Estimation for Sparse Graphs
Christian Borgs, Jennifer Chayes, Adam Smith
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Ye Wang, David B Dunson
Probabilistic Line Searches for Stochastic Optimization
Maren Mahsereci, Philipp Hennig
Probabilistic Variational Bounds for Graphical Models
Qiang Liu, John W. Fisher III, Alex Ihler
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling
Zheng Qu, Peter Richtarik, Tong Zhang