2 citations · 4 across the 4 of their papers we have counts for
5 papers
Simpliciality of strongly convex problems
Naoki Hamada, Shunsuke Ichiki
A multiobjective optimization problem is simplicial if the Pareto set and the Pareto front are diffeomorphic to a simplex and, under the diffeomorphisms, each fac…
Asymptotic Risk of Bezier Simplex Fitting
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi +1
The Bezier simplex fitting is a novel data modeling technique which exploits geometric structures of data to approximate the Pareto front of multi-objective optimization problems.…
Topology of Pareto sets of strongly convex problems
Naoki Hamada, Kenta Hayano, Shunsuke Ichiki +2
A multiobjective optimization problem is simplicial if the Pareto set and front are homeomorphic to a simplex and, under the homeomorphisms, each face of the simplex corresponds to…
Bezier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-objective Optimization
Ken Kobayashi, Naoki Hamada, Akiyoshi Sannai +3
Multi-objective optimization problems require simultaneously optimizing two or more objective functions. Many studies have reported that the solution set of an M-objective optimiza…
Simple Problems: The Simplicial Gluing Structure of Pareto Sets and Pareto Fronts
Naoki Hamada
Quite a few studies on real-world applications of multi-objective optimization reported that their Pareto sets and Pareto fronts form a topological simplex. Such a class of problem…