Publications

This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.

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16 results for Matthew Riemer

Continual Learning In Environments With Polynomial Mixing Times
- - Matthew Riemer
  - Sharath Chandra Raparthy
  - et al.
- 2022
- NeurIPS 2022
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
- - Dong Ki Kim
  - Matthew Riemer
  - et al.
- 2022
- NeurIPS 2022
Context-Specific Representation Abstraction for Deep Option Learning
- - Marwa Abdulhai
  - Dong Ki Kim
  - et al.
- 2022
- AAAI 2022
Hierarchical Average Reward Policy Gradient Algorithms
- - Akshay Dharmavaram
  - Matthew Riemer
  - et al.
- 2020
- AAAI 2020
On the role of weight sharing during deep option learning
- - Matthew Riemer
  - Ignacio Cases
  - et al.
- 2020
- AAAI 2020
Learning to learn without forgetting by maximizing transfer and minimizing interference
- - Matthew Riemer
  - Ignacio Cases
  - et al.
- 2019
- ICLR 2019
Scalable recollections for continual lifelong learning
- - Matthew Riemer
  - Tim Klinger
  - et al.
- 2019
- AAAI 2019
Learning to teach in cooperative multiagent reinforcement learning
- - Shayegan Omidshafiei
  - Dong Ki Kim
  - et al.
- 2019
- AAAI 2019
Learning abstract options
- - Matthew Riemer
  - Miao Liu
  - et al.
- 2018
- NeurIPS 2018
Routing networks: Adaptive selection of non-linear functions for multi-task learning
- - Clemens Rosenbaum
  - Tim Klinger
  - et al.
- 2018
- ICLR 2018