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» Gaussian Processes in Reinforcement Learning
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JMLR
2010
135views more  JMLR 2010»
13 years 8 months ago
Bundle Methods for Regularized Risk Minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
MP
2011
13 years 4 months ago
Null space conditions and thresholds for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
AAAI
2012
12 years 9 hour ago
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images
Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of “How to feed a hungry world?”. Unfor...
Kristian Kersting, Zhao Xu, Mirwaes Wahabzada, Chr...
ICRA
2003
IEEE
165views Robotics» more  ICRA 2003»
14 years 2 months ago
Multi-robot task-allocation through vacancy chains
Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumptio...
Torbjørn S. Dahl, Maja J. Mataric, Gaurav S...
SIGCSE
2000
ACM
132views Education» more  SIGCSE 2000»
14 years 2 months ago
Empirical investigation throughout the CS curriculum
Empirical skills are playing an increasingly important role in the computing profession and our society. But while traditional computer science curricula are effective in teaching...
David W. Reed, Craig S. Miller, Grant Braught