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Books and Theses
- 2023
[b1]Sinong Geng:
Model-Regularized Machine Learning for Decision-Making. Princeton University, USA, 2023
Journal Articles
- 2023
- [j1]Melda Alaluf, Giulia Crippa, Sinong Geng, Zijian Jing, Nikhil Krishnan, Sanjeev Kulkarni, Wyatt Navarro, Ronnie Sircar, Jonathan Tang:
Reinforcement learning paycheck optimization for multivariate financial goals. Risk Decis. Anal. 9(1): 11-18 (2023)
Conference and Workshop Papers
- 2024
- [c8]Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng:
Improving Offline RL by Blending Heuristics. ICLR 2024 - 2023
- [c7]Sinong Geng, Houssam Nassif, Carlos A. Manzanares:
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models. UAI 2023: 647-657 - 2020
- [c6]Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar:
Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions. ICML 2020: 3431-3441 - 2019
- [c5]Sinong Geng, Minhao Yan, Mladen Kolar, Sanmi Koyejo:
Partially Linear Additive Gaussian Graphical Models. ICML 2019: 2180-2190 - [c4]Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo:
Joint Nonparametric Precision Matrix Estimation with Confounding. UAI 2019: 378-388 - 2018
- [c3]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. ICML 2018: 1700-1709 - [c2]Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page:
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI 2018: 156-166 - 2017
- [c1]Zhaobin Kuang, Sinong Geng, David Page:
A Screening Rule for l1-Regularized Ising Model Estimation. NIPS 2017: 720-731
Informal and Other Publications
- 2024
- [i8]Melda Alaluf, Giulia Crippa, Sinong Geng, Zijian Jing, Nikhil Krishnan, Sanjeev Kulkarni, Wyatt Navarro, Ronnie Sircar, Jonathan Tang:
Reinforcement Learning Paycheck Optimization for Multivariate Financial Goals. CoRR abs/2403.06011 (2024) - 2023
- [i7]Sinong Geng, Houssam Nassif, Carlos A. Manzanares:
A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models. CoRR abs/2304.04916 (2023) - [i6]Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng:
Improving Offline RL by Blending Heuristics. CoRR abs/2306.00321 (2023) - 2020
- [i5]Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page:
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR abs/2005.06083 (2020) - [i4]Sinong Geng, Zhaobin Kuang, Peggy L. Peissig, David Page:
Temporal Poisson Square Root Graphical Models. CoRR abs/2005.06462 (2020) - [i3]Sinong Geng, Houssam Nassif, Carlos A. Manzanares, A. Max Reppen, Ronnie Sircar:
Identifying Reward Functions using Anchor Actions. CoRR abs/2007.07443 (2020) - 2019
- [i2]Sinong Geng, Minhao Yan, Mladen Kolar, Oluwasanmi Koyejo:
Partially Linear Additive Gaussian Graphical Models. CoRR abs/1906.03362 (2019) - 2018
- [i1]Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo:
Joint Nonparametric Precision Matrix Estimation with Confounding. CoRR abs/1810.07147 (2018)
Coauthor Index
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