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» Learning from Multiple Annotators with Gaussian Processes
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74
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ICASSP
2011
IEEE
14 years 3 months ago
Joint dictionary learning and topic modeling for image clustering
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
KDD
1998
ACM
190views Data Mining» more  KDD 1998»
15 years 4 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee
97
Voted
ICASSP
2011
IEEE
14 years 3 months ago
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme
CIVR
2006
Springer
174views Image Analysis» more  CIVR 2006»
15 years 3 months ago
Annotating News Video with Locations
Abstract. The location of video scenes is an important semantic descriptor especially for broadcast news video. In this paper, we propose a learning-based approach to annotate shot...
Jun Yang 0003, Alexander G. Hauptmann
85
Voted
AAAI
2007
15 years 2 months ago
Learning Language Semantics from Ambiguous Supervision
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
Rohit J. Kate, Raymond J. Mooney