Papers
184,605 papers found
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE
Garvesh Raskutti, Bin Yu, Martin J. Wainwright et al.
Model Selection in Kernel Based Regression using the Influence Function
Michiel Debruyne, Mia Hubert, Johan A.K. Suykens
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont
Mortal Multi-Armed Bandits
Deepayan Chakrabarti, Ravi Kumar, Filip Radlinski et al.
Multi-Agent Filtering with Infinitely Nested Beliefs
Luke Zettlemoyer, Brian Milch, Leslie P. Kaelbling
Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study
Avraham Bab, Ronen I. Brafman
Multi-class Discriminant Kernel Learning via Convex Programming
Jieping Ye, Shuiwang Ji, Jianhui Chen
Multi-label Multiple Kernel Learning
Shuiwang Ji, Liang Sun, Rong Jin et al.
Multi-Level Active Prediction of Useful Image Annotations for Recognition
Sudheendra Vijayanarasimhan, Kristen Grauman
Multi-resolution Exploration in Continuous Spaces
Ali Nouri, Michael L. Littman
Multiscale Random Fields with Application to Contour Grouping
Longin J. Latecki, Chengen Lu, Marc Sobel et al.
Multi-Sensor Lane Finding in Urban Road Networks
Albert Huang, David Moore, Matthew Antone et al.
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
Christopher Williams, Stefan Klanke, Sethu Vijayakumar et al.
NanoNewton Force Sensing and Control in Microrobotic Cell Manipulation
Xinyu Liu, Keekyoung Kim, Yong Zhang et al.
Natural Image Denoising with Convolutional Networks
Viren Jain, Sebastian Seung
Near-minimax recursive density estimation on the binary hypercube
Maxim Raginsky, Svetlana Lazebnik, Rebecca Willett et al.
Near-optimal Regret Bounds for Reinforcement Learning
Peter Auer, Thomas Jaksch, Ronald Ortner
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
Andreas Krause, Ajit Singh, Carlos Guestrin
Nonlinear causal discovery with additive noise models
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij et al.
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan et al.
Non-Parametric Modeling of Partially Ranked Data
Guy Lebanon, Yi Mao
Nonparametric regression and classification with joint sparsity constraints
Han Liu, Larry Wasserman, John D. Lafferty
Non-parametric Regression Between Manifolds
Florian Steinke, Matthias Hein