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Matthew Riemer
Matthew Riemer
IBM, Mila
Verified email at us.ibm.com
Title
Cited by
Cited by
Year
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
M Riemer, I Cases, R Ajemian, M Liu, I Rish, Y Tu, G Tesauro
Seventh International Conference on Learning Representations (ICLR 2019), 2018
6832018
Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning
C Rosenbaum, T Klinger, M Riemer
Sixth International Conference on Learning Representations (ICLR 2018), 2017
2672017
Towards Continual Reinforcement Learning: A Review and Perspectives
K Khetarpal, M Riemer, I Rish, D Precup
Journal of Artificial Intelligence Research (JAIR), 2020
2122020
Learning to Teach in Cooperative Multiagent Reinforcement Learning
S Omidshafiei, DK Kim, M Liu, G Tesauro, M Riemer, C Amato, ...
Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), 2018
1422018
Learning Abstract Options
M Riemer, M Liu, G Tesauro
Thirty-Second Conference on Neural Information Processing Systems (NIPS 2018), 2018
852018
Routing Networks and the Challenges of Modular and Compositional Computation
C Rosenbaum, I Cases, M Riemer, T Klinger
arXiv preprint arXiv:1904.12774, 2019
722019
Scalable Recollections for Continual Lifelong Learning
M Riemer, T Klinger, D Bouneffouf, M Franceschini
Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), 2017
682017
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
DK Kim, M Liu, M Riemer, C Sun, M Abdulhai, G Habibi, S Lopez-Cot, ...
Thirty-Eigth International Conference on Machine Learning (ICML 2021), 2020
572020
PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences
P Das, K Wadhawan, O Chang, T Sercu, CD Santos, M Riemer, I Padhi, ...
NIPS 2018 Workshop on Machine Learning for Molecules and Materials, 2018
552018
Learning Hierarchical Teaching Policies for Cooperative Agents
DK Kim, M Liu, S Omidshafiei, S Lopez-Cot, M Riemer, G Habibi, ...
International Conference on Autonomous Agents and Multi-Agent Systems 2020, 2019
41*2019
Correcting Forecasts with Multifactor Neural Attention
M Riemer, A Vempaty, FP Calmon, FF Heath III, R Hull, E Khabiri
Thirty-Third International Conference on Machine Learning (ICML 2016), 2016
382016
Recursive Routing Networks: Learning to Compose Modules for Language Understanding
I Cases, C Rosenbaum, M Riemer, A Geiger, T Klinger, A Tamkin, O Li, ...
Proceedings of NAACL 2019, 2019
292019
Sequoia: A software framework to unify continual learning research
F Normandin, F Golemo, O Ostapenko, P Rodriguez, MD Riemer, ...
arXiv preprint arXiv:2108.01005, 2021
19*2021
Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning
M Riemer, E Khabiri, R Goodwin
arXiv preprint arXiv:1704.03617, 2016
192016
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
DK Kim, M Riemer, M Liu, JN Foerster, M Everett, C Sun, G Tesauro, ...
Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
172022
Time series forecasting to determine relative causal impact
FD Calmon, FF Heath III, RB Hull, E Khabiri, MD Riemer, A Vempaty
US Patent 11,537,847, 2022
152022
Facilitating mapping of control policies to regulatory documents
SB Tirumala, A Jagmohan, E Khabiri, TH Li, MD Riemer, V Sheinin, ...
US Patent 10,922,621, 2021
152021
On the Role of Weight Sharing During Deep Option Learning
M Riemer, I Cases, C Rosenbaum, M Liu, G Tesauro
Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 2019
142019
Context-Specific Representation Abstraction for Deep Option Learning
M Abdulhai, DK Kim, M Riemer, M Liu, G Tesauro, JP How
Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), 2021
112021
Continual Learning with Self-Organizing Maps
P Bashivan, M Schrimpf, R Ajemian, I Rish, M Riemer, Y Tu
NIPS 2018 Workshop on Continual Learning, 2018
102018
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Articles 1–20