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ICML
2008
IEEE
16 years 4 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
142
Voted
NIPS
1998
15 years 4 months ago
Facial Memory Is Kernel Density Estimation (Almost)
We compare the ability of three exemplar-based memory models, each using three different face stimulus representations, to account for the probability a human subject responded &q...
Matthew N. Dailey, Garrison W. Cottrell, Thomas A....
CDC
2009
IEEE
156views Control Systems» more  CDC 2009»
15 years 7 months ago
Input design using Markov chains for system identification
This paper studies the input design problem for system identification where time domain constraints have to be considered. A finite Markov chain is used to model the input of the s...
Chiara Brighenti, Bo Wahlberg, Cristian R. Rojas
QEST
2006
IEEE
15 years 9 months ago
Lumping Markov Chains with Silent Steps
Jasen Markovski, Nikola Trcka
PAMI
2012
13 years 5 months ago
Probabilistic Models for Inference about Identity
—Many face recognition algorithms use “distance-based” methods: Feature vectors are extracted from each face and distances in feature space are compared to determine matches....
Simon Prince, Peng Li, Yun Fu, Umar Mohammed, Jame...