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...
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...
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...
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 ...
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...