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R. Fuji-Hara

4 papers hereh-index 121k citations46 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.CO4

identity via Semantic Scholar / OpenAlex

most citedCombinatorial Designs for Deep Learning

5 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

math.CO2023

GDD type Spanning Bipartite Block Designs

Shoko Chisaki, Ryoh Fuji-Hara, Nobuko Miyamoto

There is a one-to-one correspondence between the point set of a group divisible design (GDD) with v1​ groups of v2​ points and the edge set of a complete bipartite graph $K_{v_…

math.CO2023

Optimality and Constructions of Spanning Bipartite Block Designs

Shoko Chisaki, Ryoh Fuji-Hara, Nobuko Miyamoto

We consider a statistical problem to estimate variables (effects) that are associated with the edges of a complete bipartite graph Kv1​,v2​​=(V1​,V2​;E). Each data is ob…

math.CO2023

Ideal Secret Sharing Schemes: Combinatorial Characterizations, Certain Access Structures, and Related Geometric Problems

Ryoh Fuji-Hara, Ying Miao

An ideal secret sharing scheme is a method of sharing a secret key in some key space among a finite set of participants in such a way that only the authorized subsets of participan…

math.CO2018★ 5 cited

Combinatorial Designs for Deep Learning

Shoko Chisaki, Ryoh Fuji-Hara, Nobuko Miyamoto

Deep learning is a machine learning methodology using multi-layer neural network. A multi-layer neural network can be regarded as a chain of complete bipartite graphs. The nodes of…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.