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JMLR
2010
154views more  JMLR 2010»
13 years 3 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
KDD
2004
ACM
181views Data Mining» more  KDD 2004»
14 years 9 months ago
Column-generation boosting methods for mixture of kernels
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Jinbo Bi, Tong Zhang, Kristin P. Bennett
ICML
2008
IEEE
14 years 9 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
UAI
2000
13 years 10 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 7 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone