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ICCV
2007
IEEE
16 years 8 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
SAC
2005
ACM
16 years 7 days ago
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process
This paper presents a novel model of reinforcement learning agents. A feature of our learning agent model is to integrate analytic hierarchy process (AHP) into a standard reinforc...
Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narih...
WSC
2001
15 years 8 months ago
On improving the performance of simulation-based algorithms for average reward processes with application to network pricing
We address performance issues associated with simulationbased algorithms for optimizing Markov reward processes. Specifically, we are concerned with algorithms that exploit the re...
Enrique Campos-Náñez, Stephen D. Pat...
184
Voted
TVLSI
1998
88views more  TVLSI 1998»
15 years 6 months ago
Time multiplexed color image processing based on a CNN with cell-state outputs
—A practical system approach for time-multiplexing cellular neural network (CNN) implementations suitable for processing large and complex images using small CNN arrays is presen...
Lei Wang, José Pineda de Gyvez, Edgar S&aac...
TIT
2002
91views more  TIT 2002»
15 years 6 months ago
Hidden Markov processes
An overview of statistical and information-theoretic aspects of hidden Markov processes (HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain observe...
Yariv Ephraim, Neri Merhav