Papers
176,624 papers found
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
Sennay Ghebreab, Arnold Smeulders, Pieter Adriaans
Predicting human gaze using low-level saliency combined with face detection
Moran Cerf, Jonathan Harel, Wolfgang Einhaeuser et al.
Predicting Partial Paths from Planning Problem Parameters
Sarah Finney, Leslie Kaelbling, and Tomas Lozano-Perez
Predictive Matrix-Variate t Models
Shenghuo Zhu, Kai Yu, Yihong Gong
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters
Gavin C. Cawley, Nicola L. C. Talbot
Privacy-Preserving Belief Propagation and Sampling
Michael Kearns, Jinsong Tan, Jennifer Wortman
Probabilistic Matrix Factorization
Andriy Mnih, Ruslan Salakhutdinov
Progressive mixture rules are deviation suboptimal
Jean-yves Audibert
Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes
Sridhar Mahadevan, Mauro Maggioni
Random Features for Large-Scale Kernel Machines
Ali Rahimi, Benjamin Recht
Random Projections for Manifold Learning
Chinmay Hegde, Michael Wakin, Richard Baraniuk
Random Sampling of States in Dynamic Programming
Chris Atkeson, Benjamin Stephens
Ranking the Best Instances
Stéphan Clémençon, Nicolas Vayatis
Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing
Yuanhao Chen, Long Zhu, Chenxi Lin et al.
Receding Horizon Differential Dynamic Programming
Yuval Tassa, Tom Erez, William D. Smart
Receptive Fields without Spike-Triggering
Guenther Zeck, Matthias Bethge, Jakob H. Macke
Refinable Kernels
Yuesheng Xu, Haizhang Zhang
Regret Minimization in Games with Incomplete Information
Martin Zinkevich, Michael Johanson, Michael Bowling et al.
Regularized Boost for Semi-Supervised Learning
Ke Chen, Shihai Wang
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach
José M. Hernández-lobato, Tjeerd Dijkstra, Tom Heskes
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
Relational Dependency Networks
Jennifer Neville, David Jensen
Retrieved context and the discovery of semantic structure
Vinayak Rao, Marc Howard
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
Zakria Hussain, François Laviolette, Mario Marchand et al.
Robust Regression with Twinned Gaussian Processes
Andrew Naish-guzman, Sean Holden