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» Sampling Methods for Unsupervised Learning
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SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 12 days ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
EMNLP
2006
15 years 11 days ago
Unsupervised Discovery of a Statistical Verb Lexicon
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...
Trond Grenager, Christopher D. Manning
CVPR
2012
IEEE
13 years 1 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
CVPR
2008
IEEE
16 years 1 months ago
Context-aware clustering
Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
Junsong Yuan, Ying Wu
CVPR
2005
IEEE
16 years 1 months ago
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Non-Overlapping Cameras
This paper proposes a novel method for matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem: p...
Ying Shan, Harpreet S. Sawhney, Rakesh Kumar