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» A new look at state-space models for neural data
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BMCBI
2010
122views more  BMCBI 2010»
13 years 10 months ago
Genome3D: A viewer-model framework for integrating and visualizing multi-scale epigenomic information within a three-dimensional
Background: New technologies are enabling the measurement of many types of genomic and epigenomic information at scales ranging from the atomic to nuclear. Much of this new data i...
Thomas M. Asbury, Matt Mitman, Jijun Tang, W. Jim ...
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
14 years 10 months ago
A multinomial clustering model for fast simulation of computer architecture designs
Computer architects utilize simulation tools to evaluate the merits of a new design feature. The time needed to adequately evaluate the tradeoffs associated with adding any new fe...
Kaushal Sanghai, Ting Su, Jennifer G. Dy, David R....
ENTCS
2006
116views more  ENTCS 2006»
13 years 10 months ago
Stepwise Refinement of Processes
Industry is looking to create a market in reliable "plug-and-play" components. To model components in a modular style it would be useful to combine event-based and state...
Steve Reeves, David Streader
JMLR
2010
140views more  JMLR 2010»
13 years 5 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 10 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle