activity
20142017
most citedEfficient SimRank Computation via Linearization

16 citations · 24 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2023

Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks

Abdalgader Abubaker, Takanori Maehara, Madhav Nimishakavi +1

Recently, pretraining methods for the Graph Neural Networks (GNNs) have been successful at learning effective representations from unlabeled graph data. However, most of these meth…

cs.DS20172 cited

Exact Computation of Influence Spread by Binary Decision Diagrams

Takanori Maehara, Hirofumi Suzuki, Masakazu Ishihata

Evaluating influence spread in social networks is a fundamental procedure to estimate the word-of-mouth effect in viral marketing. There are enormous studies about this topic; howe…

stat.ML20164 cited

Finding Alternate Features in Lasso

Satoshi Hara, Takanori Maehara

We propose a method for finding alternate features missing in the Lasso optimal solution. In ordinary Lasso problem, one global optimum is obtained and the resulting features are i…

cs.GT20161 cited

Optimal Pricing for Submodular Valuations with Bounded Curvature

Takanori Maehara, Yasushi Kawase, Hanna Sumita +2

The optimal pricing problem is a fundamental problem that arises in combinatorial auctions. Suppose that there is one seller who has indivisible items and multiple buyers who want…

cs.CL2014

Learning Word Representations from Relational Graphs

Danushka Bollegala, Takanori Maehara, Yuichi Yoshida +1

Attributes of words and relations between two words are central to numerous tasks in Artificial Intelligence such as knowledge representation, similarity measurement, and analogy d…

cs.DS201416 cited

Efficient SimRank Computation via Linearization

Takanori Maehara, Mitsuru Kusumoto, Ken-ichi Kawarabayashi

SimRank, proposed by Jeh and Widom, provides a good similarity measure that has been successfully used in numerous applications. While there are many algorithms proposed for comput…