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ICML
2003
IEEE
14 years 8 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
ISCA
2008
IEEE
137views Hardware» more  ISCA 2008»
14 years 2 months ago
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach
Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deli...
Engin Ipek, Onur Mutlu, José F. Martí...
AUSAI
2008
Springer
13 years 9 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe
IJCV
2007
196views more  IJCV 2007»
13 years 7 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone