Papers
PAC-Bayesian AUC classification and scoring
James Ridgway, Pierre Alquier, Nicolas Chopin et al.
Parallel Direction Method of Multipliers
Huahua Wang, Arindam Banerjee, Zhi-Quan Luo
Parallel Double Greedy Submodular Maximization
Xinghao Pan, Stefanie Jegelka, Joseph E Gonzalez et al.
Parallel Feature Selection Inspired by Group Testing
Yingbo Zhou, Utkarsh Porwal, Ce Zhang et al.
Parallel Sampling of HDPs using Sub-Cluster Splits
Jason Chang, John W. Fisher III
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo et al.
Partition-wise Linear Models
Hidekazu Oiwa, Ryohei Fujimaki
Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision
Deepti Pachauri, Risi Kondor, Gautam Sargur et al.
Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data
Florian Stimberg, Andreas Ruttor, Manfred Opper
Positive Curvature and Hamiltonian Monte Carlo
Christof Seiler, Simon Rubinstein-Salzedo, Susan Holmes
Predicting Useful Neighborhoods for Lazy Local Learning
Aron Yu, Kristen Grauman
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions
José Miguel Hernández-Lobato, Matthew W Hoffman, Zoubin Ghahramani
Pre-training of Recurrent Neural Networks via Linear Autoencoders
Luca Pasa, Alessandro Sperduti
Probabilistic Differential Dynamic Programming
Yunpeng Pan, Evangelos Theodorou
Probabilistic low-rank matrix completion on finite alphabets
Jean Lafond, Olga Klopp, Eric Moulines et al.
Probabilistic ODE Solvers with Runge-Kutta Means
Michael Schober, David K. Duvenaud, Philipp Hennig
Projecting Markov Random Field Parameters for Fast Mixing
Xianghang Liu, Justin Domke
Projective dictionary pair learning for pattern classification
Shuhang Gu, Lei Zhang, Wangmeng Zuo et al.
Provable Submodular Minimization using Wolfe's Algorithm
Deeparnab Chakrabarty, Prateek Jain, Pravesh Kothari
Provable Tensor Factorization with Missing Data
Prateek Jain, Sewoong Oh
Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators
Kai Zhong, Ian En-Hsu Yen, Inderjit S Dhillon et al.
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls
Yuancheng Zhu, John Lafferty
Quantized Kernel Learning for Feature Matching
Danfeng Qin, Xuanli Chen, Matthieu Guillaumin et al.
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models
Cho-Jui Hsieh, Inderjit S Dhillon, Pradeep K Ravikumar et al.