Kei Ota

Joined

October 2020

Names

Kei Ota (Preferred)

Emails

****@gmail.com (Confirmed)

****@m.titech.ac.jp

****@merl.com (Confirmed)

****@ds.mitsubishielectric.co.jp

Personal Links

Career & Education History

PhD student

Tokyo Institute of Technology, Tokyo Institute of Technology (titech.ac.jp)

2021 – 2024

MS student

Tokyo Institute of Technology, Tokyo Institute of Technology (titech.ac.jp)

2015 – 2017

Undergrad student

Tokyo Institute of Technology, Tokyo Institute of Technology (titech.ac.jp)

2011 – 2015

Advisors, Relations & Conflicts

Coauthor

Krishna Murthy Jatavallabhula

2022 – Present

PhD Advisor

Asako Kanezaki

2019 – Present

Coauthor

Joshua B. Tenenbaum

2019 – Present

Coauthor

Kevin A Smith

2019 – Present

Coworker

Devesh K. Jha

2018 – Present

Coworker

Daniel N. Nikovski

2018 – Present

Expertise

reinforcement learning

2017 – Present

robot learning

2017 – Present

Publications

Sim-to-Real Contact-Rich Pivoting via Optimization-Guided RL with Vision and Touch
Yuki Shirai, Kei Ota, Devesh K. Jha, Diego Romeres
- NeurIPS 2025 Workshop EWM
- Readers: Everyone
Tactile-Filter: Interactive Tactile Perception for Part Mating
Kei Ota, Devesh K. Jha, Hsiao-Yu Tung, Joshua B. Tenenbaum
- 2023 (modified: 18 Apr 2023)
- CoRR 2023
- Readers: Everyone
OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching
Hana Hoshino, Kei Ota, Asako Kanezaki, Rio Yokota
- 2022 (modified: 01 Nov 2022)
- ICRA 2022
- Readers: Everyone
Object Memory Transformer for Object Goal Navigation
Rui Fukushima, Kei Ota, Asako Kanezaki, Yoko Sasaki, Yusuke Yoshiyasu
- 2022 (modified: 10 Nov 2022)
- ICRA 2022
- Readers: Everyone
H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions
Kei Ota, Hsiao-Yu Tung, Kevin A. Smith, Anoop Cherian, Tim K. Marks, Alan Sullivan, Asako Kanezaki, Joshua B. Tenenbaum
- 2022 (modified: 02 Apr 2023)
- CoRR 2022
- Readers: Everyone
Training Larger Networks for Deep Reinforcement Learning
Kei Ota, Devesh K. Jha, Asako Kanezaki
- 2021 (modified: 11 Jun 2022)
- CoRR 2021
- Readers: Everyone
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving Using Augmented Simulation
Kei Ota, Devesh K. Jha, Diego Romeres, Jeroen van Baar, Kevin A. Smith, Takayuki Semitsu, Tomoaki Oiki, Alan Sullivan, Daniel Nikovski, Joshua B. Tenenbaum
- 2021 (modified: 18 Apr 2023)
- IEEE Robotics Autom. Lett. 2021
- Readers: Everyone
Deep Reactive Planning in Dynamic Environments
Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski
- 2020 (modified: 10 Nov 2022)
- CoRL 2020
- Readers: Everyone
Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path
Kei Ota, Yoko Sasaki, Devesh K. Jha, Yusuke Yoshiyasu, Asako Kanezaki
- 2020 (modified: 10 Nov 2022)
- IROS 2020
- Readers: Everyone
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski
- 2020 (modified: 18 Apr 2023)
- ICML 2020
- Readers: Everyone

View all 11 publications

Kei Ota

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Co-Authors