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ISDA
2010
IEEE
13 years 6 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
APPROX
2009
Springer
142views Algorithms» more  APPROX 2009»
14 years 3 months ago
Optimal Sherali-Adams Gaps from Pairwise Independence
Abstract. This work considers the problem of approximating fixed predicate constraint satisfaction problems (MAX k-CSP(P)). We show that if the set of assignments accepted by P co...
Konstantinos Georgiou, Avner Magen, Madhur Tulsian...
AI
2007
Springer
14 years 3 months ago
Adding Local Constraints to Bayesian Networks
When using Bayesian networks, practitioners often express constraints among variables by conditioning a common child node to induce the desired distribution. For example, an ‘or...
Mark Crowley, Brent Boerlage, David Poole
JMLR
2008
230views more  JMLR 2008»
13 years 8 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
TIP
2008
109views more  TIP 2008»
13 years 8 months ago
Iterative Rate-Distortion Optimization of H.264 With Constant Bit Rate Constraint
In this paper, we apply the primal-dual decomposition and subgradient projection methods to solve the rate-distortion optimization problem with the constant bit rate constraint. Th...
Cheolhong An, Truong Q. Nguyen