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CGF
2010
189views more  CGF 2010»
13 years 6 months ago
Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
ICML
2003
IEEE
14 years 6 months ago
Exploration in Metric State Spaces
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Sham Kakade, Michael J. Kearns, John Langford
ICMLA
2008
13 years 7 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa
CODES
2008
IEEE
14 years 13 days ago
Static analysis for fast and accurate design space exploration of caches
Application-specific system-on-chip platforms create the opportunity to customize the cache configuration for optimal performance with minimal chip estate. Simulation, in partic...
Yun Liang, Tulika Mitra
CSDA
2006
191views more  CSDA 2006»
13 years 6 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms