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NIPS
2007
13 years 6 months ago
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Charlie Frogner, Avi Pfeffer
BICOB
2009
Springer
13 years 2 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
BMCBI
2007
160views more  BMCBI 2007»
13 years 5 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
EH
2005
IEEE
127views Hardware» more  EH 2005»
13 years 10 months ago
On the Robustness Achievable with Stochastic Development Processes
Manufacturing processes are a key source of faults in complex hardware systems. Minimizing this impact of manufacturing uncertainties is one way towards achieving fault tolerant s...
Shivakumar Viswanathan, Jordan B. Pollack
EUROMICRO
2009
IEEE
13 years 8 months ago
Synthetic Metrics for Evaluating Runtime Quality of Software Architectures with Complex Tradeoffs
Runtime quality of software, such as availability and throughput, depends on architectural factors and execution environment characteristics (e.g. CPU speed, network latency). Alth...
Anakreon Mentis, Panagiotis Katsaros, Lefteris Ang...