I am a 3rd-year doctoral course student at University of Tokyo. My supervisor is Prof. Satoru Iwata.
I stayed at ETH Zurich from mid-January to mid-April in 2019. The host researcher is Prof. Andreas Krause.
Email: kaito_fujii + at + mist.i.u-tokyo.ac.jp
dblp google scholar
Research Interests
My research interests lie in the intersection of combinatorial optimization and machine learning.I am particularly interested in submodular maximization, adaptive optimization, optimal stopping theory, and online learning.
Refereed Publications
- Kaito Fujii and Shinsaku Sakaue
Beyond adaptive submodularity: Approximation guarantees of greedy policy with adaptive submodularity ratio
Proceedings of the 36th International Conference on Machine Learning (ICML), pp. 2042--2051, 2019.
[poster] [slides] - Kaito Fujii and Tasuku Soma (alphabetical order)
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
Advances in Neural Information Processing Systems (NeurIPS), 31, pp. 4745--4754, 2018. Spotlight (top 4% submissions).
[poster] [spotlight slides] - Kaito Fujii and Hisashi Kashima
Budgeted stream-based active learning via adaptive submodular maximization
Advances in Neural Information Processing Systems (NIPS), 29, pp. 514--522, 2016. - Kaito Fujii
Faster approximation algorithms for maximizing a monotone submodular function subject to a b-matching constraint
Information Processing Letters, 116(9), pp. 578--584, 2016.
Preprints
- Kaito Fujii
An improved algorithm for the submodular secretary problem with a cardinality constraint
ArXiv preprints, 2019. - Kaito Fujii, Tasuku Soma, and Yuichi Yoshida (alphabetical order)
Polynomial-time algorithms for submodular Laplacian systems
ArXiv preprints, 2018.