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CSDA
2007
94views more  CSDA 2007»
13 years 8 months ago
Some extensions of score matching
Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then h...
Aapo Hyvärinen
ICASSP
2011
IEEE
13 years 13 days ago
Point process MCMC for sequential music transcription
In this paper, models and algorithms are presented for transcription of pitch and timings in polyphonic music extracts, focusing on the algorithm details of the sequential Markov ...
Pete Bunch, Simon J. Godsill
NIPS
2001
13 years 10 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
ACL
1994
13 years 10 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
VALUETOOLS
2006
ACM
164views Hardware» more  VALUETOOLS 2006»
14 years 2 months ago
Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
Kai Lampka, Markus Siegle