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William R. Zame
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2020 – today
- 2022
- [c16]Alihan Hüyük, William R. Zame, Mihaela van der Schaar:
Inferring Lexicographically-Ordered Rewards from Preferences. AAAI 2022: 5737-5745 - [i17]Alihan Hüyük, William R. Zame, Mihaela van der Schaar:
Inferring Lexicographically-Ordered Rewards from Preferences. CoRR abs/2202.10153 (2022) - 2021
- [c15]Hyun-Suk Lee, Cong Shen, William R. Zame, Jang-Won Lee, Mihaela van der Schaar:
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups. AISTATS 2021: 2980-2988 - [c14]Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul W. G. Elbers, Mihaela van der Schaar:
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression. NeurIPS 2021: 11364-11383 - [i16]Hyun-Suk Lee, Cong Shen, William R. Zame, Jang-Won Lee, Mihaela van der Schaar:
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups. CoRR abs/2101.10998 (2021) - [i15]Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul W. G. Elbers, Mihaela van der Schaar:
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression. CoRR abs/2106.02875 (2021) - 2020
- [c13]Jonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar:
Learning outside the Black-Box: The pursuit of interpretable models. NeurIPS 2020 - [c12]Hyun-Suk Lee, Yao Zhang, William R. Zame, Cong Shen, Jang-Won Lee, Mihaela van der Schaar:
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification. NeurIPS 2020 - [i14]Hyun-Suk Lee, Yao Zhang, William R. Zame, Cong Shen, Jang-Won Lee, Mihaela van der Schaar:
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification. CoRR abs/2006.07917 (2020) - [i13]Yao Zhang, William R. Zame, Mihaela van der Schaar:
AutoNCP: Automated pipelines for accurate confidence intervals. CoRR abs/2006.14099 (2020) - [i12]Jonathan Crabbé
, Yao Zhang, William R. Zame, Mihaela van der Schaar:
Learning outside the Black-Box: The pursuit of interpretable models. CoRR abs/2011.08596 (2020)
2010 – 2019
- 2019
- [j12]Onur Atan, William R. Zame, Qiaojun Feng
, Mihaela van der Schaar
:
Constructing effective personalized policies using counterfactual inference from biased data sets with many features. Mach. Learn. 108(6): 945-970 (2019) - [j11]Jinsung Yoon
, William R. Zame, Mihaela van der Schaar
:
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks. IEEE Trans. Biomed. Eng. 66(5): 1477-1490 (2019) - [c11]Kartik Ahuja, William R. Zame, Mihaela van der Schaar:
Optimal Piecewise Approximations for Model Interpretation. ACSSC 2019: 1992-1998 - [c10]Changhee Lee, William R. Zame, Ahmed M. Alaa, Mihaela van der Schaar:
Temporal Quilting for Survival Analysis. AISTATS 2019: 596-605 - [c9]Onur Atan, William R. Zame, Mihaela van der Schaar:
Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials. AISTATS 2019: 1891-1900 - 2018
- [j10]Jinsung Yoon
, William R. Zame, Mihaela van der Schaar
:
ToPs: Ensemble Learning With Trees of Predictors. IEEE Trans. Signal Process. 66(8): 2141-2152 (2018) - [c8]Changhee Lee, William R. Zame, Jinsung Yoon, Mihaela van der Schaar:
DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks. AAAI 2018: 2314-2321 - [c7]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks. ICLR (Poster) 2018 - [i11]Onur Atan, William R. Zame, Mihaela van der Schaar:
Learning Optimal Policies from Observational Data. CoRR abs/1802.08679 (2018) - [i10]Kartik Ahuja, William R. Zame, Mihaela van der Schaar:
Piecewise Approximations of Black Box Models for Model Interpretation. CoRR abs/1806.10270 (2018) - [i9]Onur Atan, William R. Zame, Mihaela van der Schaar:
Adaptive Clinical Trials: Exploiting Sequential Patient Recruitment and Allocation. CoRR abs/1810.02876 (2018) - 2017
- [c6]Kartik Ahuja, William R. Zame, Mihaela van der Schaar:
DPSCREEN: Dynamic Personalized Screening. NIPS 2017: 1321-1332 - [i8]Jinsung Yoon, William R. Zame, Amitava Banerjee, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar:
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors. CoRR abs/1704.03458 (2017) - [i7]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
ToPs: Ensemble Learning with Trees of Predictors. CoRR abs/1706.01396 (2017) - [i6]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks. CoRR abs/1711.08742 (2017) - 2016
- [i5]Onur Atan, William R. Zame, Qiaojun Feng, Mihaela van der Schaar:
Constructing Effective Personalized Policies Using Counterfactual Inference from Biased Data Sets with Many Features. CoRR abs/1612.08082 (2016) - 2014
- [j9]William R. Zame, Jie Xu
, Mihaela van der Schaar
:
Cooperative Multi-Agent Learning and Coordination for Cognitive Radio Networks. IEEE J. Sel. Areas Commun. 32(3): 464-477 (2014) - [j8]Yuanzhang Xiao, William R. Zame, Mihaela van der Schaar
:
Technology Choices and Pricing Policies in Public and Private Wireless Networks. IEEE Trans. Wirel. Commun. 13(12): 6606-6618 (2014) - 2013
- [j7]William R. Zame, Jie Xu
, Mihaela van der Schaar
:
Winning the Lottery: Learning Perfect Coordination With Minimal Feedback. IEEE J. Sel. Top. Signal Process. 7(5): 846-857 (2013) - [j6]Luca Canzian, Yuanzhang Xiao, William R. Zame, Michele Zorzi, Mihaela van der Schaar
:
Intervention with Private Information, Imperfect Monitoring and Costly Communication. IEEE Trans. Commun. 61(8): 3192-3205 (2013) - [j5]Luca Canzian, Yuanzhang Xiao, William R. Zame, Michele Zorzi, Mihaela van der Schaar
:
Intervention with Complete and Incomplete Information: Application to Flow Control. IEEE Trans. Commun. 61(8): 3206-3218 (2013) - [c5]William R. Zame, Jie Xu
, Mihaela van der Schaar
:
Learning perfect coordination with minimal feedback in wireless multi-access communications. GLOBECOM 2013: 3861-3866 - [i4]Mihaela van der Schaar, Yuanzhang Xiao, William R. Zame:
Designing Efficient Resource Sharing For Impatient Players Using Limited Monitoring. CoRR abs/1309.0262 (2013) - 2012
- [j4]Khoa Tran Phan, Mihaela van der Schaar, William R. Zame:
Congestion, Information, and Secret Information in Flow Networks. IEEE J. Sel. Top. Signal Process. 6(2): 117-126 (2012) - [c4]Jie Xu, William R. Zame, Mihaela van der Schaar:
Token economy for online exchange systems. AAMAS 2012: 1283-1284 - [c3]Jie Xu
, William R. Zame, Mihaela van der Schaar:
Token-Based Incentive Protocol Design for Online Exchange Systems. GAMENETS 2012: 248-258 - [i3]Luca Canzian, Yuanzhang Xiao, William R. Zame, Michele Zorzi, Mihaela van der Schaar:
Designing Information Revelation and Intervention with an Application to Flow Control. CoRR abs/1207.4044 (2012) - 2011
- [c2]Khoa Tran Phan, Mihaela van der Schaar, William R. Zame:
Secret information in communications networks. CDC/ECC 2011: 3110-3115 - [c1]Yuanzhang Xiao, William R. Zame, Mihaela van der Schaar:
Technology Choices and Pricing Policies in Wireless Networks. GAMENETS 2011: 92-107 - [i2]Jie Xu, Mihaela van der Schaar, William R. Zame:
Designing Exchange for Online Communities. CoRR abs/1108.5871 (2011) - 2010
- [i1]Yuanzhang Xiao, William R. Zame, Mihaela van der Schaar:
Technology Choices and Pricing Policies in Public and Private Wireless Networks. CoRR abs/1011.3580 (2010)
2000 – 2009
- 2005
- [j3]Christopher J. Harris, Maxwell B. Stinchcombe, William R. Zame:
Nearly compact and continuous normal form games: characterizations and equilibrium existence. Games Econ. Behav. 50(2): 208-224 (2005) - 2001
- [j2]Bryan Ellickson, Birgit Grodal, Suzanne Scotchmer, William R. Zame:
Clubs and the Market: Large Finite Economies. J. Econ. Theory 101(1): 40-77 (2001)
1990 – 1999
- 1997
- [j1]Elaine Bennett, Michael Maschler, William R. Zame:
A demand adjustment process. Int. J. Game Theory 26(4): 423-438 (1997)
Coauthor Index
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