Bio
I completed my PhD in mathematics at the Courant Institute of Mathematical Sciences.
From 2015 to 2017, I co-organized the NYU Machine Learning Seminar.
In 2013 and 2014, I co-directed Courant Splash, a STEM outreach event for high-school students organized by the Courant Institute.
Publications
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Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri and Scott Yang.
Online Learning with Sleeping Experts and Feedback Graphs.
In Proceedings of the 36th International Conference on Machine Learning (ICML 2019). Long Beach, California. June 2019.
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Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Dmitry Storcheus and Scott Yang.
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses.
In Advances in Neural Information Processing Systems (NeurIPS 2018). Montreal, Canada. December 2018.
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Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri and Scott Yang.
Online Learning with Abstensions.
In Proceedings of the 35th International Conference on Machine Learning (ICML 2018). Stockholm, Sweden. July 2018.
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Mehryar Mohri and Scott Yang.
Competing with Automata-based Expert Sequences. (oral presentation).
In 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018). Lanzarote, Spain, April 2018.
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Mehryar Mohri and Scott Yang.
Online Learning with Transductive Regret. (spotlight presentation).
In Advances in Neural Information Processing Systems (NIPS 2017). Long Beach, California. December 2017.
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Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri and Scott Yang.
AdaNet: Adaptive Structural Learning of Artificial Neural Networks.
In Proceedings of the 34th International Conference on Machine Learning (ICML 2017). Sydney, Australia. August 2017.
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Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri and Scott Yang.
Structured Prediction Theory Based on Factor Graph Complexity.
In Advances in Neural Information Processing Systems (NIPS 2016). Barcelona, Spain. December 2016.
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Mehryar Mohri and Scott Yang.
Optimistic Bandit Convex Optimization.
In Advances in Neural Information Processing Systems (NIPS 2016). Barcelona, Spain. December 2016.
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Mehryar Mohri and Scott Yang.
Structural Online Learning.
In Proceedings of the 27th International Conference on Algorithmic Learning Theory (ALT 2016). Bari, Italy. October 2016.
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Mehryar Mohri and Scott Yang.
Adaptive Algorithms and Data-dependent Guarantees for Bandit Convex Optimization.
In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2016) . Jersey City, New Jersey. June 2016.
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Andrez Munoz Medina and Scott Yang.
No-Regret Algorithms for Heavy-Tailed Linear Bandits.
In Proceedings of the 33rd International Conference on Machine Learning (ICML 2016). New York, New York. June 2016.
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Mehryar Mohri and Scott Yang.
Accelerating Optimization via Adaptive Prediction.
In 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016). Cádiz, Spain, May 2016.
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Mehryar Mohri and Scott Yang.
Conditional Swap Regret and Conditional Correlated Equilibrium.
In Advances in Neural Information Processing Systems (NIPS 2014). Montreal, Canada. December 2014.
Workshops, symposia, and other presentations
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AdaNet: Adaptive Structural Learning of Artificial Neural Networks (Best Spotlight Award).
11th Annual Machine Learning Symposium at the New York Academy of Sciences . New York, New York. March 2017.
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Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, and Scott Yang.
AdaNet: Adaptive Structural Learning of Artificial Neural Networks.
NIPS 2016 Workshop on Efficient Methods for Deep Neural Networks. Barcelona, Spain. December 2016.
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Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, and Scott Yang.
AdaNet: Adaptive Structural Learning of Artificial Neural Networks.
NIPS 2016 Workshop on Adaptive and Scalable Nonparametric Methods in Machine Learning. Barcelona, Spain. December 2016.
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Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, and Scott Yang.
A Theoretical Framework for Structured Prediction using Factor Graph Complexity (spotlight presentation).
NIPS 2016 Workshop on Extreme Classification. Barcelona, Spain. December 2016.
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Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, and Scott Yang.
Measuring Learnability in Structured Prediction using Factor Graph Complexity (spotlight presentation).
NIPS 2016 Workshop on Learning in High Dimensions with Structure. Barcelona, Spain. December 2016.
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Accelerating Optimization via Adaptive Prediction.
Informs Optimization Society Conference 2016. Princeton, New Jersey. February 2016.
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Mehryar Mohri and Scott Yang.
Accelerating Optimization via Adaptive Prediction.
NIPS 2015 Workshop on Optimization. Montreal, Canada. December 2015.
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Mehryar Mohri and Scott Yang.
Accelerating Optimization: Pre-empting the Leader via Adaptive Prediction (spotlight presentation).
NIPS 2015 Workshop on Learning Faster from Easy Data. Montreal, Canada. December 2015.
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Mehryar Mohri and Scott Yang.
Data-Dependent Algorithms for Bandit Convex Optimization (spotlight presentation).
NIPS 2015 Workshop on Learning Faster from Easy Data. Montreal, Canada. December 2015.
Service and other activities
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Co-organizer:
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ICML 2019 Time Series Workshop
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NIPS 2017 Time Series Workshop
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ICML 2017 Time Series Workshop
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Program committee member:
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Reviewer:
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NIPS: 2014, 2015, 2016, 2017 (Best Reviewer Award), 2018 (Best Reviewer Award)
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ICML: 2016, 2017, 2018 (Outstanding Reviewer), 2019
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ICLR: 2018, 2019
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AAAI: 2016, 2017
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COLT: 2016, 2017
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ALT: 2016
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JMLR
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TCS
Teaching
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Advanced Machine Learning (Teaching Assistant, NYU Spring 2017).
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Foundations of Machine Learning (Teaching Assistant, NYU Fall 2016).
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Foundations of Machine Learning (Teaching Assistant, NYU Fall 2015).
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Foundations of Machine Learning (Teaching Assistant, NYU Fall 2014).
Contact
- E-mail: yangs[at]cims[dot]nyu[dot]edu