788 citations
- T. Koike-Akino17 · h 32
- Takaaki Hori16 · h 40
- Jonathan Le Roux3 profiles14 · h 47
- Shinji Watanabe14 · h 86
- Devesh K. Jha2 profiles10 · h 21
- Ye Wang3 profiles10 · h 21
- A. Raghunathan8 · h 30
- P. Boufounos8 · h 30
- Chungwei Lin2 profiles7 · h 24
- Yanting Ma2 profiles7 · h 11
- Deniz Erdoğmuş6 · h 61
- D. Nikovski6 · h 26
- Mitsubishi Electric Research Laboratories (United States)US67 papers
- Mitsubishi Electric (Japan)JP14 papers
- Johns Hopkins UniversityUS13 papers
- Carnegie Mellon UniversityUS8 papers
- New York UniversityUS7 papers
- Harvard UniversityUS6 papers
- Northeastern UniversityUS6 papers
- Shanghai Jiao Tong UniversityCN6 papers
- Boston UniversityUS5 papers
- Columbia UniversityUS5 papers
- Massachusetts Institute of TechnologyUS5 papers
- Flatiron Health (United States)US4 papers
7 papers · 2 filters
Learning on Attribute-Missing Graphs
Xu Chen, Siheng Chen, Jiangchao Yao +3
Graphs with complete node attributes have been widely explored recently. While in practice, there is a graph where attributes of only partial nodes could be available and those of…
Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation
Kei Ota, Devesh K. Jha, Diego Romeres +7
Humans quickly solve tasks in novel systems with complex dynamics, without requiring much interaction. While deep reinforcement learning algorithms have achieved tremendous success…
Semi-Supervised Speech Recognition via Graph-based Temporal Classification
Niko Moritz, Takaaki Hori, Jonathan Le Roux
Semi-supervised learning has demonstrated promising results in automatic speech recognition (ASR) by self-training using a seed ASR model with pseudo-labels generated for unlabeled…
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction
Mo Han, Ozan Ozdenizci, Ye Wang +2
Recent developments in biosignal processing have enabled users to exploit their physiological status for manipulating devices in a reliable and safe manner. One major challenge of…
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context
Wenyu Zhang, Skyler Seto, Devesh K. Jha
Learning accurate models of the physical world is required for a lot of robotic manipulation tasks. However, during manipulation, robots are expected to interact with unknown workp…
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh K. Jha +2
Deep reinforcement learning (RL) algorithms have recently achieved remarkable successes in various sequential decision making tasks, leveraging advances in methods for training lar…