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» Parameterized Complexity and Approximation Algorithms
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GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 2 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
100
Voted
SMA
1999
ACM
152views Solid Modeling» more  SMA 1999»
15 years 2 months ago
Fast volume-preserving free form deformation using multi-level optimization
We present an efficient algorithm for preserving the total volume of a solids undergoing free-form deformation using discrete level-of-detail representations. Given the boundary r...
Gentaro Hirota, Renee Maheshwari, Ming C. Lin
81
Voted
CPM
1999
Springer
92views Combinatorics» more  CPM 1999»
15 years 2 months ago
Physical Mapping with Repeated Probes: The Hypergraph Superstring Problem
We focus on the combinatorial analysis of physical mapping with repeated probes. We present computational complexity results, and we describe and analyze an algorithmic strategy. W...
Serafim Batzoglou, Sorin Istrail
67
Voted
COCO
1998
Springer
98views Algorithms» more  COCO 1998»
15 years 2 months ago
Probabilistic Martingales and BPTIME Classes
We define probabilistic martingales based on randomized approximation schemes, and show that the resulting notion of probabilistic measure has several desirable robustness propert...
Kenneth W. Regan, D. Sivakumar
89
Voted
NIPS
2008
14 years 11 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...