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» Sampling Methods for Unsupervised Learning
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CVPR
2008
IEEE
16 years 5 months ago
Two-Dimensional Active Learning for image classification
In this paper, we propose a two-dimensional active learning scheme and show its application in image classification. Traditional active learning methods select samples only along ...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang,...
AR
2007
105views more  AR 2007»
15 years 3 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
ICML
2008
IEEE
16 years 3 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 4 months ago
Semi-supervised Feature Selection via Spectral Analysis
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Zheng Zhao, Huan Liu
DCC
2005
IEEE
16 years 2 months ago
The Markov Expert for Finding Episodes in Time Series
We describe a domain-independent, unsupervised algorithm for refined segmentation of time series data into meaningful episodes, focusing on the problem of text segmentation. The V...
Jimming Cheng, Michael Mitzenmacher