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 InterestsMy 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.
- 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.
- 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.
- 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.