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» Hierarchical Gaussian process latent variable models
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ICASSP
2011
IEEE
14 years 7 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen
IJON
2010
140views more  IJON 2010»
15 years 2 months ago
Multi-task preference learning with an application to hearing aid personalization
We present an EM-algorithm for the problem of learning preferences with Gaussian processes in the context of multi-task learning. We validate our approach on an audiological data ...
Adriana Birlutiu, Perry Groot, Tom Heskes
131
Voted
ICML
2006
IEEE
16 years 4 months ago
Collaborative ordinal regression
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborati...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
SIGIR
2003
ACM
15 years 9 months ago
Modeling annotated data
We consider the problem of modeling annotated data—data with multiple types where the instance of one type (such as a caption) serves as a description of the other type (such as...
David M. Blei, Michael I. Jordan
CVPR
2012
IEEE
13 years 6 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller