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PAA
2008
15 years 4 months ago
A sparse Bayesian approach for joint feature selection and classifier learning
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
Àgata Lapedriza, Santi Seguí, David ...
ECML
2004
Springer
15 years 9 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
ICML
1995
IEEE
16 years 5 months ago
Learning to Make Rent-to-Buy Decisions with Systems Applications
In the single rent-to-buy decision problem, without a priori knowledge of the amount of time a resource will be used we need to decide when to buy the resource, given that we can ...
P. Krishnan, Philip M. Long, Jeffrey Scott Vitter
IBPRIA
2009
Springer
15 years 9 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
SIAMDM
2010
117views more  SIAMDM 2010»
15 years 2 months ago
Design is as Easy as Optimization
We consider the class of max-min and min-max optimization problems subject to a global budget (or weight) constraint and we undertake a systematic algorithmic and complexitytheore...
Deeparnab Chakrabarty, Aranyak Mehta, Vijay V. Vaz...