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» Semi-Supervised Learning of Mixture Models
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CDC
2008
IEEE
15 years 9 months ago
Shannon meets Bellman: Feature based Markovian models for detection and optimization
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
Sean P. Meyn, George Mathew
AAAI
2010
15 years 4 months ago
A Bayesian Nonparametric Approach to Modeling Mobility Patterns
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...
UAI
2003
15 years 4 months ago
Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
Darya Chudova, Scott Gaffney, Padhraic Smyth
NIPS
2003
15 years 4 months ago
Non-linear CCA and PCA by Alignment of Local Models
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
ICASSP
2010
IEEE
15 years 3 months ago
Sound source separation in monaural music signals using excitation-filter model and em algorithm
This paper proposes a method for separating the signals of individual musical instruments from monaural musical audio. The mixture signal is modeled as a sum of the spectra of ind...
Anssi Klapuri, Tuomas Virtanen, Toni Heittola