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CRV
2009
IEEE
115views Robotics» more  CRV 2009»
15 years 7 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
138
Voted
RECOMB
2009
Springer
16 years 1 months ago
Learning Models for Aligning Protein Sequences with Predicted Secondary Structure
Accurately aligning distant protein sequences is notoriously difficult. A recent approach to improving alignment accuracy is to use additional information such as predicted seconda...
Eagu Kim, Travis J. Wheeler, John D. Kececioglu
SIGMOD
2006
ACM
219views Database» more  SIGMOD 2006»
16 years 29 days ago
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Flip Korn, S. Muthukrishnan, Yihua Wu
115
Voted
CIBCB
2007
IEEE
15 years 7 months ago
Modeling protein-DNA binding time in Stochastic Discrete Event Simulation of Biological Processes
Abstract— This paper presents a parametric model to estimate the DNA-protein binding time using the DNA and protein structures and details of the binding site. To understand the ...
Preetam Ghosh, Samik Ghosh, Kalyan Basu, Sajal K. ...
CDC
2009
IEEE
185views Control Systems» more  CDC 2009»
15 years 5 months ago
Discrete Empirical Interpolation for nonlinear model reduction
A dimension reduction method called Discrete Empirical Interpolation (DEIM) is proposed and shown to dramatically reduce the computational complexity of the popular Proper Orthogo...
Saifon Chaturantabut, Danny C. Sorensen