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» A Spectral Algorithm for Learning Hidden Markov Models
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SECON
2007
IEEE
14 years 1 months ago
Analysis of Search Schemes in Cognitive Radio
— Cognitive Radio systems face an important challenge – fast and reliable channel searching to enable secondary users to optimize available spectral resources. We revisit conve...
Ling Luo, S. Roy
COLT
2004
Springer
14 years 1 months ago
Learning a Hidden Graph Using O(log n) Queries Per Edge
We consider the problem of learning a general graph using edge-detecting queries. In this model, the learner may query whether a set of vertices induces an edge of the hidden grap...
Dana Angluin, Jiang Chen
NIPS
1997
13 years 9 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
PE
2010
Springer
138views Optimization» more  PE 2010»
13 years 6 months ago
Trace data characterization and fitting for Markov modeling
We propose a trace fitting algorithm for Markovian Arrival Processes (MAPs) that can capture statistics of any order of interarrival times between measured events. By studying re...
Giuliano Casale, Eddy Z. Zhang, Evgenia Smirni
ICMLA
2009
13 years 5 months ago
Structured Prediction Models for Chord Transcription of Music Audio
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the not...
Adrian Weller, Daniel P. W. Ellis, Tony Jebara