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ALT
2006
Springer
16 years 3 months ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
UAI
2008
15 years 7 months ago
Convex Point Estimation using Undirected Bayesian Transfer Hierarchies
When related learning tasks are naturally arranged in a hierarchy, an appealing approach for coping with scarcity of instances is that of transfer learning using a hierarchical Ba...
Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne ...
ML
2008
ACM
15 years 6 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
DIS
2010
Springer
15 years 4 months ago
Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships
Quantitative structure-activity relationships (QSARs) are regression models relating chemical structure to biological activity. Such models allow to make predictions for toxicologi...
Ulrich Rückert, Tobias Girschick, Fabian Buch...
CVPR
2007
IEEE
16 years 8 months ago
Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition
Outdoor face recognition is among the most challenging problems for face recognition. In this paper, we develop a discriminant mutual subspace learning algorithm for indoor and ou...
Zhifeng Li, Dahua Lin, Helen M. Meng, Xiaoou Tang