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GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 1 months ago
Innovization: innovating design principles through optimization
This paper introduces a new design methodology (we call it "innovization") in the context of finding new and innovative design principles by means of optimization techni...
Kalyanmoy Deb, Aravind Srinivasan
DAGM
2004
Springer
15 years 2 months ago
Predictive Discretization During Model Selection
We present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive the joint scoring function from the principle of p...
Harald Steck, Tommi Jaakkola
99
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AGENTS
1999
Springer
15 years 1 months ago
General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
David Wolpert, Kevin R. Wheeler, Kagan Tumer
UAI
2004
14 years 10 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
ICML
2006
IEEE
15 years 10 months ago
Generalized spectral bounds for sparse LDA
We present a discrete spectral framework for the sparse or cardinality-constrained solution of a generalized Rayleigh quotient. This NPhard combinatorial optimization problem is c...
Baback Moghaddam, Yair Weiss, Shai Avidan