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101
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STOC
2004
ACM
102views Algorithms» more  STOC 2004»
16 years 2 months ago
A simple polynomial-time rescaling algorithm for solving linear programs
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
John Dunagan, Santosh Vempala
86
Voted
VMCAI
2005
Springer
15 years 8 months ago
Termination of Polynomial Programs
We present a technique to prove termination of multipath polynomial programs, an expressive class of loops that enables practical traction and analysis. The technique is based on ï...
Aaron R. Bradley, Zohar Manna, Henny B. Sipma
105
Voted
ICMLA
2007
15 years 4 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
ENTCS
2006
125views more  ENTCS 2006»
15 years 2 months ago
Estimating the Cost of Native Method Calls for Resource-bounded Functional Programming Languages
We address the problem of applying resource-bounded functional programming languages in practice on object-oriented virtual machines which include calls to native methods coded in...
Stephen T. Gilmore, Olha Shkaravska
GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
15 years 12 days ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson