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ICML
2007
IEEE
16 years 7 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
ICML
2006
IEEE
16 years 7 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
ICML
2002
IEEE
16 years 7 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICALT
2006
IEEE
16 years 20 days ago
The e-Learning Assessment Landscape
Assessment is one of the more established areas of e-learning. However, it cannot be described as mature due to the disparate nature of the tools and standards available. As part ...
David E. Millard, Christopher Bailey, Hugh C. Davi...
COLT
2006
Springer
15 years 10 months ago
A Randomized Online Learning Algorithm for Better Variance Control
We propose a sequential randomized algorithm, which at each step concentrates on functions having both low risk and low variance with respect to the previous step prediction functi...
Jean-Yves Audibert