Coming Events

The prototype selection problem aims to learn a sparse distribution of a source set such that it best matches a different target set. The applications of this problem include target subset selection, data summarization, and clustering, to name a few. In this talk, we present efficient algorithms for the prototype selection problem. Using the optimal transport theory, the proposed optimization formulation is an instance of submodular maximization, and therefore, we propose a greedy algorithm with simple updates. We further make use of the bandit setup to reduce the computations. The presentation is based on the papers [1, 2].

1. SPOT: A Framework for Selection of Prototypes Using Optimal Transport | SpringerLink, ECML 2021.
2. [2210.01860] ProtoBandit: Efficient Prototype Selection via Multi-Armed Bandits (arxiv.org), ACML 2022.

Design thinking is a problem-solving approach that is used to develop innovative and user-centered solutions. It is a process that helps individuals and teams to understand the needs and perspectives of users, and to develop solutions that meet those needs in a creative and effective way.