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» Machine learning problems from optimization perspective
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GECCO
2005
Springer
162views Optimization» more  GECCO 2005»
15 years 7 months ago
An autonomous explore/exploit strategy
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...
Alex McMahon, Dan Scott, William N. L. Browne
IJIT
2004
15 years 3 months ago
Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
SMC
2007
IEEE
125views Control Systems» more  SMC 2007»
15 years 8 months ago
Scaling with digital connection: Services innovation
—Digitization of production factors, including the knowledge for knowledge workers and consumers, opens almost infinite potential to connect persons, systems, processes, enterpri...
Cheng Hsu
JMLR
2008
230views more  JMLR 2008»
15 years 2 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...
GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
15 years 6 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay