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DiJia Su
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Books and Theses
- 2022
- [b1]DiJia Su:
Topics in Machine Learning. Princeton University, USA, 2022
Journal Articles
- 2023
- [j1]DiJia Su
, Difei Su, John M. Mulvey, H. Vincent Poor
:
Optimizing Multidocument Summarization by Blending Reinforcement Learning Policies. IEEE Trans. Artif. Intell. 4(3): 416-427 (2023)
Conference and Workshop Papers
- 2022
- [c4]DiJia Su, Jason D. Lee, John M. Mulvey, H. Vincent Poor:
Competitive Multi-Agent Reinforcement Learning with Self-Supervised Representation. ICASSP 2022: 4098-4102 - [c3]DiJia Andy Su, Bertrand Douillard, Rami Al-Rfou, Cheol Park, Benjamin Sapp:
Narrowing the coordinate-frame gap in behavior prediction models: Distillation for efficient and accurate scene-centric motion forecasting. ICRA 2022: 653-659 - 2020
- [c2]Dijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier:
ConQUR: Mitigating Delusional Bias in Deep Q-Learning. ICML 2020: 9187-9195 - 2015
- [c1]DiJia Su, S. A. Mousavifar, C. Leung:
Secrecy capacity and wireless energy harvesting in amplify-and-forward relay networks. PACRIM 2015: 258-262
Informal and Other Publications
- 2022
- [i4]DiJia Su, Bertrand Douillard, Rami Al-Rfou, Cheolho Park, Benjamin Sapp:
Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting. CoRR abs/2206.03970 (2022) - [i3]Zihan Ding, Dijia Su, Qinghua Liu, Chi Jin:
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games. CoRR abs/2207.08894 (2022) - 2021
- [i2]DiJia Su, Jason D. Lee, John M. Mulvey, H. Vincent Poor:
MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning. CoRR abs/2102.11448 (2021) - [i1]DiJia Andy Su, Difei Su, John M. Mulvey, H. Vincent Poor:
PoBRL: Optimizing Multi-Document Summarization by Blending Reinforcement Learning Policies. CoRR abs/2105.08244 (2021)
Coauthor Index
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