Umar Syed

Research Scientist
Google
111 8th Avenue 4th Fl.
New York, NY 10011

Curriculum Vitae

I am a research scientist at Google. I received a Ph.D. in Computer Science from Princeton University, where I was advised by Rob Schapire. I spent two years as a postdoctoral researcher at the University of Pennsylvania, hosted by Ben Taskar and Michael Kearns. My research interests are in machine learning.

Publications

Balkanski, E., Syed, U., Vassilvitskii, S. (2017)* Statistical cost sharing. Advances in Neural Information Processing Systems 30 (NIPS 2017).
Nazerzadeh, H., Paes Leme, R., Rostamizadeh, A., Syed, U. (2016)* Where to sell: Simulating auctions from learning algorithms. Proceedings of the Seventeenth ACM Conference on Economics and Computation (EC 2016).
Heidari, H., Mahdian, M., Syed, U., Vassilvitskii, S., Yazdanbod, S. (2016)* Pricing a low-regret seller. Proceedings of the Thirty-Third International Conference on Machine Learning (ICML 2016).
Choromanski, K., Rostamizadeh, A., Syed, U. (2015)* An optimal online algorithm for retrieving heavily perturbed statistical databases in the low-dimensional querying model. Proceedings of the Twenty-Fourth ACM International Conference on Information and Knowledge Management (CIKM 2015).
DeSalvo, G., Mohri, M., Syed, U. (2015)* Learning with deep cascades. Proceedings of the Twenty-Sixth International Conference on Algorithmic Learning Theory (ALT 2015).
Cortes, C., Kuznetsov, V., Mohri, M., Syed, U. (2015)* Structural maxent models. Proceedings of the Thirty-Second International Conference on Machine Learning (ICML 2015). Supplement.
Kuznetsov, V., Mohri, M., Syed, U. (2014)* Multi-class deep boosting. Advances in Neural Information Processing Systems 27 (NIPS 2014). Supplement.
Amin, K., Rostamizadeh, A., Syed, U. (2014)* Repeated contextual auctions with strategic buyers. Advances in Neural Information Processing Systems 27 (NIPS 2014). Supplement.
Cortes, C., Mohri, M., Syed, U. (2014)* Deep boosting. Proceedings of the Thirty-First International Conference on Machine Learning (ICML 2014). Supplement.
Asuncion, A., de Haan, J., Mohri, M., Patel, K., Rostamizadeh, A., Syed, U., Wong, L. (2014)* Corporate learning at scale: Lessons from a large online course at Google. Learning at Scale 2014.
Amin, K., Rostamizadeh, A., Syed, U. (2013)* Learning prices for repeated auctions with strategic buyers. Advances in Neural Information Processing Systems 26 (NIPS 2013). Supplement.
Amin, K., Kearns, M., Syed, U. (2011)* Graphical models for bandit problems. Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Seventh Conference (UAI 2011).
Amin, K., Kearns, M., Syed, U. (2011)* Bandits, query learning, and the haystack dimension. Proceedings of the Twenty-Fourth Annual Conference on Learning Theory (COLT 2011).
Fabrikant, A., Syed, U., Rexford, J. (2011) There's something about MRAI: Timing diversity can exponentially worsen BGP convergence. Proceedings of the Thirtieth IEEE International Conference on Computer Communications (INFOCOM 2011).
Syed, U., Taskar, B. (2010) Semi-supervised learning with adversarially missing label information. Advances in Neural Information Processing Systems 23 (NIPS 2010). Supplement.
Syed, U., Schapire, R. E. (2010) A reduction from apprenticeship learning to classification. Advances in Neural Information Processing Systems 23 (NIPS 2010).
Brautbar, M., Kearns, M., Syed, U. (2010)* Private and third-party randomization in risk-sensitive equilibrium concepts. Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI 2010).
Syed, U. (2010) Reinforcement learning without rewards. Ph.D. thesis. Department of Computer Science, Princeton University.
Syed, U., Slivkins, A., Mishra, N. (2009) Adapting to the shifting intent of search queries. Advances in Neural Information Processing Systems 22 (NIPS 2009). Full version
Syed, U., Bowling, M., Schapire, R. E. (2008) Apprenticeship learning using linear programming. Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML 2008).
Syed, U., Williams, J. D. (2008) Using automatically transcribed dialogs to learn user models in a spoken dialog system. Proceedings of the Forty-Sixth Annual Meeting of the Association for Computational Linguistics (ACL 2008).
Syed, U., Yona, G. (2008) Enzyme function prediction with interpretable models. Methods in Molecular Biology: Computational Systems Biology, edited by J. McDermott, K. Montgomery, R. Bumgarner and R. Samudrala. Humana Press. [Book chapter]
Syed, U., Schapire, R. E. (2007) A game-theoretic approach to apprenticeship learning. Advances in Neural Information Processing Systems 20 (NIPS 2007). Supplement and videos.
Syed, U., Schapire, R. E. (2007) Imitation learning with a value-based prior. Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Third Conference (UAI 2007).
Syed, U., Yona, G. (2003) Using a mixture of probabilistic decisions trees for direct prediction of protein function. Proceedings of the Seventh Annual International Conference on Research in Computational Biology (RECOMB 2003).
* Denotes alphabetical author order.

Code

Apprenticeship learning code associated with the above NIPS 2007 and ICML 2008 papers (includes highway simulator).