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» Algorithms for Challenging Motif Problems
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JMLR
2012
13 years 7 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
SPLC
2008
15 years 6 months ago
Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
Jules White, B. Doughtery, Douglas C. Schmidt
STOC
2010
ACM
195views Algorithms» more  STOC 2010»
15 years 8 months ago
Efficiently Learning Mixtures of Two Gaussians
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We provide a polynomial-time algorithm for this proble...
Adam Tauman Kalai, Ankur Moitra, and Gregory Valia...
140
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IJAR
2008
83views more  IJAR 2008»
15 years 4 months ago
Decision-theoretic specification of credal networks: A unified language for uncertain modeling with sets of Bayesian networks
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Credal nets appear to be power...
Alessandro Antonucci, Marco Zaffalon
SASO
2010
IEEE
15 years 2 months ago
Distributed Control for Small Customer Energy Demand Management
We present the ColoredPower algorithm, which is designed to provide collaborative electricity demand shaping for residential and small-business customers. Demand shaping for this m...
Vinayak V. Ranade, Jacob Beal