In calculus and related areas of mathematics, a linear function from the real numbers to the real numbers is a function whose graph (in Cartesianâ€¦Â (More)

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2009

2009

- JesÃºs M. Jorge
- European Journal of Operational Research
- 2009

Optimizing a linear function over the efficient set of a multiobjective integer linear programming (MOILP) problem is a topic ofâ€¦Â (More)

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2009

2009

- Guang Yong Zou, Wenyi Huang, Xiaohe Zhang
- Computational Statistics & Data Analysis
- 2009

The Wilson score confidence interval for a binomial proportion has been widely applied in practice, due largely to its goodâ€¦Â (More)

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2008

2008

Editorâ€™s Summary: This chapter considers temporal difference algorithms within the context of infinite-horizon finite-stateâ€¦Â (More)

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2008

2008

- Dusa Mcduff, SUSAN TOLMAN, Vladlen Timorin
- 2008

We analyze mass linear functions on simple polytopes âˆ†, where a mass linear function is an affine function on âˆ† whose value onâ€¦Â (More)

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2006

2006

- Moncef Abbas, Djamal Chaabane
- European Journal of Operational Research
- 2006

In this paper, a method for optimizing a linear function over the integer Pareto-optimal set without having to determine allâ€¦Â (More)

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2006

2006

- Gerald G. Brown
- 2006

Applications in operations research often employ models which contain linear functions. These linear functions may have someâ€¦Â (More)

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2002

2002

- Ralf Schoknecht
- NIPS
- 2002

There are several reinforcement learning algorithms that yield approximate solutions for the problem of policy evaluation whenâ€¦Â (More)

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2000

2000

This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance ofâ€¦Â (More)

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1996

1996

- Alan M. Frieze, Mark Jerrum, Ravi Kannan
- FOCS
- 1996

We present a polynomial time algorithm to learn (in Valiant's PAC model) cubes in n? space (with general sides-not necessarilyâ€¦Â (More)

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Highly Cited

1990

Highly Cited

1990

- W. Eric L. Grimson, Daniel P. Huttenlocher
- ICCV
- 1990

Geometric Hashing is a technique for recognizing partially occluded objects from noisy data. It uses ofline preprocessing toâ€¦Â (More)

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