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ML
2007
ACM
144views Machine Learning» more  ML 2007»
14 years 9 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
SAC
2008
ACM
14 years 9 months ago
Supporting self-organization for hybrid grid resource scheduling
Increasing scale, dynamism, and complexity of hybrid grids make traditional grid resource scheduling approaches difficult. In such grids, where resource volatility and dynamism is...
Deger Cenk Erdil, Michael J. Lewis
IBERAMIA
2010
Springer
14 years 8 months ago
Dynamic Reward Shaping: Training a Robot by Voice
Reinforcement Learning is commonly used for learning tasks in robotics, however, traditional algorithms can take very long training times. Reward shaping has been recently used to ...
Ana C. Tenorio-Gonzalez, Eduardo F. Morales, Luis ...
IEEECIT
2010
IEEE
14 years 8 months ago
Exploiting More Parallelism from Applications Having Generalized Reductions on GPU Architectures
Reduction is a common component of many applications, but can often be the limiting factor for parallelization. Previous reduction work has focused on detecting reduction idioms a...
Xiao-Long Wu, Nady Obeid, Wen-Mei Hwu
IJCV
2010
158views more  IJCV 2010»
14 years 8 months ago
Metric Learning for Image Alignment
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
Minh Hoai Nguyen, Fernando De la Torre