Papers
Newton-Like Methods for Sparse Inverse Covariance Estimation
Figen Oztoprak, Jorge Nocedal, Steven Rennie et al.
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates
Zhihua Zhang, Bojun Tu
Non-linear Metric Learning
Dor Kedem, Stephen Tyree, Fei Sha et al.
Non-parametric Approximate Dynamic Programming via the Kernel Method
Nikhil Bhat, Vivek Farias, Ciamac C. Moallemi
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions
Jaedeug Choi, Kee-eung Kim
Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction
Minjie Xu, Jun Zhu, Bo Zhang
Nonparametric Reduced Rank Regression
Rina Foygel, Michael Horrell, Mathias Drton et al.
Nonparanormal Belief Propagation (NPNBP)
Gal Elidan, Cobi Cario
No-Regret Algorithms for Unconstrained Online Convex Optimization
Brendan Mcmahan, Matthew Streeter
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison
Tianbao Yang, Yu-feng Li, Mehrdad Mahdavi et al.
One Permutation Hashing
Ping Li, Art Owen, Cun-hui Zhang
On Lifting the Gibbs Sampling Algorithm
Deepak Venugopal, Vibhav Gogate
Online allocation and homogeneous partitioning for piecewise constant mean-approximation
Alexandra Carpentier, Odalric-ambrym Maillard
Online L1-Dictionary Learning with Application to Novel Document Detection
Shiva P. Kasiviswanathan, Huahua Wang, Arindam Banerjee et al.
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
Ronald Ortner, Daniil Ryabko
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization
Andre Barreto, Doina Precup, Joelle Pineau
Online Sum-Product Computation Over Trees
Mark Herbster, Stephen Pasteris, Fabio Vitale
On Multilabel Classification and Ranking with Partial Feedback
Claudio Gentile, Francesco Orabona
On the connections between saliency and tracking
Vijay Mahadevan, Nuno Vasconcelos
On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking
Clément Calauzènes, Nicolas Usunier, Patrick Gallinari
On the Sample Complexity of Robust PCA
Matthew Coudron, Gilad Lerman
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes
Bruno Scherrer, Boris Lesner
On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks
Qirong Ho, Junming Yin, Eric P. Xing
Optimal kernel choice for large-scale two-sample tests
Arthur Gretton, Dino Sejdinovic, Heiko Strathmann et al.
Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss
Zhuo Wang, Alan Stocker, Daniel D Lee