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» On Learning Mixtures of Heavy-Tailed Distributions
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ICCS
2007
Springer
14 years 2 months ago
Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces
New architectures for Brain-Machine Interface communication and control use mixture models for expanding rehabilitation capabilities of disabled patients. Here we present and test ...
Jack DiGiovanna, Loris Marchal, Prapaporn Rattanat...
AAAI
2010
13 years 9 months ago
A Two-Dimensional Topic-Aspect Model for Discovering Multi-Faceted Topics
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
Michael Paul, Roxana Girju
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 9 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
ICPR
2002
IEEE
14 years 9 months ago
Fractional Component Analysis (FCA) for Mixed Signals
This paper proposes the fractional component analysis (FCA), whose goal is to decompose the observed signal into component signals and recover their fractions. The uniqueness of o...
Asanobu Kitamoto
ICA
2007
Springer
14 years 14 days ago
Phase-Aware Non-negative Spectrogram Factorization
Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixtur...
R. Mitchell Parry, Irfan A. Essa