Papers
On Poisson Graphical Models
Eunho Yang, Pradeep K Ravikumar, Genevera I Allen et al.
On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori Perturbations
Tamir Hazan, Subhransu Maji, Tommi Jaakkola
On the Complexity and Approximation of Binary Evidence in Lifted Inference
Guy Van den Broeck, Adnan Darwiche
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
Ke Hou, Zirui Zhou, Anthony Man-Cho So et al.
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation
Harikrishna Narasimhan, Shivani Agarwal
On the Representational Efficiency of Restricted Boltzmann Machines
James Martens, Arkadev Chattopadhya, Toni Pitassi et al.
On the Sample Complexity of Subspace Learning
Alessandro Rudi, Guillermo D Canas, Lorenzo Rosasco
Optimal integration of visual speed across different spatiotemporal frequency channels
Matjaz Jogan, Alan Stocker
Optimal Neural Population Codes for High-dimensional Stimulus Variables
Zhuo Wang, Alan Stocker, Daniel D Lee
Optimistic Concurrency Control for Distributed Unsupervised Learning
Xinghao Pan, Joseph E Gonzalez, Stefanie Jegelka et al.
Optimization, Learning, and Games with Predictable Sequences
Sasha Rakhlin, Karthik Sridharan
Optimizing Instructional Policies
Robert Lindsey, Michael Mozer, William J Huggins et al.
PAC-Bayes-Empirical-Bernstein Inequality
Ilya O Tolstikhin, Yevgeny Seldin
Parallel Sampling of DP Mixture Models using Sub-Cluster Splits
Jason Chang, John W. Fisher III
Parametric Task Learning
Ichiro Takeuchi, Tatsuya Hongo, Masashi Sugiyama et al.
Pass-efficient unsupervised feature selection
Crystal Maung, Haim Schweitzer
Perfect Associative Learning with Spike-Timing-Dependent Plasticity
Christian Albers, Maren Westkott, Klaus Pawelzik
Phase Retrieval using Alternating Minimization
Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs
Liam C MacDermed, Charles L Isbell
Polar Operators for Structured Sparse Estimation
Xinhua Zhang, Yao-Liang Yu, Dale Schuurmans
Policy Shaping: Integrating Human Feedback with Reinforcement Learning
Shane Griffith, Kaushik Subramanian, Jonathan Scholz et al.
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh et al.
Predictive PAC Learning and Process Decompositions
Cosma Shalizi, Aryeh Kontorovich
Prior-free and prior-dependent regret bounds for Thompson Sampling
Sebastien Bubeck, Che-Yu Liu