Speaker: Ryoh Fuji-Hara（University of Tsukuba）
Time: Nov 29, 2024, 10:00-11:00
Location: Room M4009, College of Science Building，Tencent Meeting ID: 995 677 362
Abstract
We are inspired by an application in deep learning called the DropConnect method, which sparses edges in a complete bipartite graph (connections) to avoid overfitting, and its application to experimental design to improve estimation accuracy. We propose a combinatorial problem called Spanning Bipartite Block Design (SBBD) and show how to construct designs that satisfy the combinatorial requirements of SBBD.
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