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TNN
2010
176views Management» more  TNN 2010»
13 years 4 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
ICASSP
2011
IEEE
13 years 1 months ago
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learn
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yas...
AAAI
2012
12 years 3 days ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
ICDAR
2009
IEEE
13 years 7 months ago
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
CVPR
2010
IEEE
13 years 7 months ago
Adaptive pose priors for pictorial structures
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
Benjamin Sapp, Chris Jordan, Ben Taskar