Machine Learning

2017
Eric Balkanski, Aviad Rubinstein, and Yaron Singer. 2017. “The Limitations of Optimization from Samples.” In ACM Symposium on the Theory of Computing (STOC 2017). Download
2016
Panos Toulis and David C. Parkes. 2016. “Long-term causal effects via behavioral game theory.” In Annual Conference on Neural Information Processing Systems (NIPS). Download
Harikrishna Narasimhan and David C. Parkes. 2016. “A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms.” In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI'16). Download
2015
Jean Pouget-Abadie and Thibaut Horel. 2015. “Inferring Graphs from Cascades: A Sparse Recovery Framework.” In Proceedings of the 32nd International Conference on Machine Learning, (ICML 2015), 977-986. Download
Harikrishna Narasimhan, David C. Parkes, and Yaron Singer. 2015. “Learnability of Influence in Networks.” In Proceedings of the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), 3186-3194. Download
2014
Hossein Azari Soufiani, David C. Parkes, and Lirong Xia. 2014. “Computing Parametric Ranking Models via Rank-Breaking.” In Proceedings of the International Conference on Machine Learning (ICML 2014), 360-368. Download
Hossein Azari Soufiani, David C. Parkes, and Lirong Xia. 2014. “A Statistical Decision-Theoretic Framework for Social Choice.” In Proceedings of the Advances in Neural Information Processing Systems 27 (NIPS 2014), 3185-3193. Download
2013
James Zou, Daniel Hsu, David C. Parkes, and Ryan P. Adams. 2013. “Contrastive Learning Using Spectral Methods.” In Proceedings of the Annual Conference on Neural Information Processing Systems (NIPS 2013), 2238-2246. Download
Panos Toulis and Edward Kao. 2013. “Estimation of Causal Peer Influence Effects.” In Proceedings of the International Conference on Machine Learning (ICML-13), 1489-1497. Download
Hossein Azari Soufiani, William Chen, David C. Parkes, and Lirong Xia. 2013. “Generalized Method-of-Moments for Rank Aggregation.” In Proceedings of the Annual Conference on Neural Information Processing Systems (NIPS 2013), 2706-2714. Download
Hossein Azari Soufiani, Hansheng Diao, Zhenyu Lai, and David C. Parkes. 2013. “Generalized Random Utility Models with Multiple Types.” In Proceedings of the Annual Conference on Neural Information Processing Systems (NIPS 2013), 73-81. Download
Hossein Azari Soufiani, David C. Parkes, and Lirong Xia. 2013. “Preference Elicitation For General Random Utility Models.” In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence (UAI-13). Download
2012
Yiling Chen, Mike Ruberry, and Jennifer Wortman Vaughan. 2012. “Designing Informative Securities.” In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI '12), 185-195. Download
James Zou and David C. Parkes. 2012. “Get another worker? Active crowdlearning with sequential arrivals.” In Proceedings of the Workshop on Machine Learning in Human Computation and Crowdsourcing(ICML'12). Download
Hossein Azari Soufiani, David C. Parkes, and Lirong Xia. 2012. “Random Utility Theory for Social Choice.” In Proceeedings of the 25th Annual Conference on Neural Information Processing Systems (NIPS'12), 126-134. Download
2010
Xi Alice Gao and Avi Pfeffer. 2010. “Learning Game Representations from Data Using Rationality Constraints.” In Proceedings of the 26th Conference on on Uncertainty in Artificial Intelligence (UAI'10). Download
Jacob Abernethy, Yiling Chen, and Jennifer Wortman Vaughan. 2010. “An Optimization-Based Framework for Automated Maket-Making.” In NIPS Workshop on Computational Social Science and the Wisdom of Crowds. Download
2008
Erik Schultink, Ruggiero Cavallo, and David C. Parkes. 2008. “Economic hierarchical Q-learning.” In Proc. 23rd AAAI Conference on Artificial Intelligence (AAAI'08), 689–695. Download
Sevan Ficici, David C. Parkes, and Avi Pfeffer. 2008. “Learning and solving many-player games through a cluster-based representation.” In Proc. 24th Conference in Uncertainty in Artificial Intelligence (UAI'08), 187–195. Download
2007
Yiling Chen and David M. Pennock. 2007. “A Utility Framework for Bounded-Loss Market Makers.” In Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence (UAI'07), 49–56. Download

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