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» Learning from Multiple Annotators with Gaussian Processes
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ICASSP
2011
IEEE
12 years 11 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»
13 years 11 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
ICASSP
2011
IEEE
12 years 11 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»
13 years 11 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
AAAI
2007
13 years 9 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