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 | 807 | 2018 |
Towards Continual Reinforcement Learning: A Review and Perspectives K Khetarpal, M Riemer, I Rish, D Precup Journal of Artificial Intelligence Research (JAIR), 2020 | 301 | 2020 |
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 | 280 | 2017 |
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 | 155 | 2018 |
Learning Abstract Options M Riemer, M Liu, G Tesauro Thirty-Second Conference on Neural Information Processing Systems (NIPS 2018), 2018 | 93 | 2018 |
Routing Networks and the Challenges of Modular and Compositional Computation C Rosenbaum, I Cases, M Riemer, T Klinger arXiv preprint arXiv:1904.12774, 2019 | 86 | 2019 |
Scalable Recollections for Continual Lifelong Learning M Riemer, T Klinger, D Bouneffouf, M Franceschini Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), 2017 | 76 | 2017 |
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 | 64 | 2018 |
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 | 63 | 2020 |
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 | 43* | 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 | 38 | 2016 |
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 | 30 | 2019 |
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 | 22* | 2021 |
Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning M Riemer, E Khabiri, R Goodwin arXiv preprint arXiv:1704.03617, 2016 | 20 | 2016 |
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 | 19 | 2022 |
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 | 18 | 2022 |
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 | 17 | 2021 |
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 | 16 | 2019 |
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 | 12 | 2021 |
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 | 10 | 2018 |