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ICMLA
2009
13 years 9 months ago
A Syllable-Level Probabilistic Framework for Bird Species Identification
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...
Balaji Lakshminarayanan, Raviv Raich, Xiaoli Fern
ICML
2007
IEEE
15 years 18 min ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
ALT
2010
Springer
14 years 22 days ago
A Lower Bound for Learning Distributions Generated by Probabilistic Automata
Known algorithms for learning PDFA can only be shown to run in time polynomial in the so-called distinguishability
Borja Balle, Jorge Castro, Ricard Gavaldà
ECML
2006
Springer
14 years 2 months ago
Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
CONCUR
2010
Springer
14 years 9 days ago
Learning I/O Automata
Links are established between three widely used modeling frameworks for reactive systems: the ioco theory of Tretmans, the interface automata of De Alfaro and Henzinger, and Mealy ...
Fides Aarts, Frits W. Vaandrager