NeurIPS 2007
217 papers
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
A learning framework for nearest neighbor search
Lawrence Cayton, Sanjoy Dasgupta
Inferring Elapsed Time from Stochastic Neural Processes
Misha Ahrens, Maneesh Sahani
The Tradeoffs of Large Scale Learning
Léon Bottou, Olivier Bousquet
Scan Strategies for Meteorological Radars
Victoria Manfredi, Jim Kurose
A Bayesian Model of Conditioned Perception
Alan Stocker, Eero P. Simoncelli
Regret Minimization in Games with Incomplete Information
Martin Zinkevich, Michael Johanson, Michael Bowling, Carmelo Piccione
Efficient Principled Learning of Thin Junction Trees
Anton Chechetka, Carlos Guestrin
Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data
Sabri Boutemedjet, Djemel Ziou, Nizar Bouguila
FilterBoost: Regression and Classification on Large Datasets
Joseph K. Bradley, Robert E. Schapire
Stable Dual Dynamic Programming
Tao Wang, Michael Bowling, Dale Schuurmans, Daniel J. Lizotte
Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Alan S. Willsky, Erik B. Sudderth, Martin J. Wainwright
Predictive Matrix-Variate t Models
Shenghuo Zhu, Kai Yu, Yihong Gong
Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains
Andrea Lecchini-visintini, John Lygeros, Jan Maciejowski
Compressed Regression
Shuheng Zhou, Larry Wasserman, John D. Lafferty
Random Features for Large-Scale Kernel Machines
Ali Rahimi, Benjamin Recht
An Analysis of Convex Relaxations for MAP Estimation
Pawan Mudigonda, Vladimir Kolmogorov, Philip Torr