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ICTAC
2005
Springer
15 years 9 months ago
Maximum Marking Problems with Accumulative Weight Functions
We present a new derivation of efficient algorithms for a class of optimization problems called maximum marking problems. We extend the class of weight functions used in the speci...
Isao Sasano, Mizuhito Ogawa, Zhenjiang Hu
GECCO
2009
Springer
147views Optimization» more  GECCO 2009»
15 years 8 months ago
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed
The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions defined on a continuous search space in a black-box scenario. In this paper, an i...
Anne Auger, Nikolaus Hansen
FLAIRS
2001
15 years 5 months ago
A Lattice-Based Approach to Hierarchical Clustering
The paper presents an approach to hierarchical clustering based on the use of a least general generalization (lgg) operator to induce a lattice structure of clusters and a categor...
Zdravko Markov
AAAI
2006
15 years 5 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht
ICASSP
2009
IEEE
15 years 10 months ago
A framework for distributed multimedia stream mining systems using coalition-based foresighted strategies
In this paper, we propose a distributed solution to the problem of configuring classifier trees in distributed stream mining systems. The configuration involves selecting appro...
Hyunggon Park, Deepak S. Turaga, Olivier Verscheur...