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COLT
1998
Springer
13 years 12 months ago
Improved Boosting Algorithms using Confidence-Rated Predictions
Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...
Robert E. Schapire, Yoram Singer
ICML
1996
IEEE
14 years 8 months ago
On the Learnability of the Uncomputable
Within Valiant'smodel of learning as formalized by Kearns, we show that computable total predicates for two formallyuncomputable problems the classical Halting Problem, and t...
Richard H. Lathrop
CVPR
2006
IEEE
14 years 9 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
IJCAI
2003
13 years 9 months ago
Covariant Policy Search
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
J. Andrew Bagnell, Jeff G. Schneider
ICASSP
2010
IEEE
13 years 7 months ago
A minimax approach to Bayesian estimation with partial knowledge of the observation model
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
Tomer Michaeli, Yonina C. Eldar