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» Sampling Methods for Unsupervised Learning
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ECML
2007
Springer
15 years 8 months ago
Roulette Sampling for Cost-Sensitive Learning
In this paper, we propose a new and general preprocessor algorithm, called CSRoulette, which converts any cost-insensitive classification algorithms into cost-sensitive ones. CSRou...
Victor S. Sheng, Charles X. Ling
ICDAR
2005
IEEE
15 years 8 months ago
Prototype Learning Methods for Online Handwriting Recognition
In this paper, we study different methods for prototype selection for recognizing handwritten characters of Tamil script. In the first method, cumulative pairwise- distances of th...
B. S. Raghavendra, C. K. Narayanan, G. Sita, A. G....
COLING
2010
14 years 9 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 6 days 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
SIGIR
2011
ACM
14 years 5 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...