[虞嘉圓]
Jia Yuan, Yu
Associate Professor, Concordia Institute of Information System Engineering.
Mailing address: |
Concordia University
1455 de Maisonneuve Blvd. West EV007.635
Montreal, Quebec H3G 1M8
Canada. |
Tel.: |
+1 514 848 2424 ext. 2873 |
e-mail: |
jiayuan.yu@concordia.ca |
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Research
I'm interested in data science and decision theory (machine learning, statistics, control, game theory, operations research), as well as applications to smart cities and Internet-connected devices.
Open Positions
I'm looking for undergraduate and graduate students to work on exciting projects involving a mix of theory, data, and prototype-building. If you have a strong background in mathematics or programming, then please feel free to email me your CV and a description of your interests.
Publications
Latest papers are on arXiv, older ones below.
Conference papers
- Transition-based and State-based Reward Functions for MDPs with Value-at-Risk, with Shuai Ma, Allerton 2017.
- The Merits of Sharing a Ride, with Pooyan Ehsani, Allerton 2017.
- A Method for Fair Assignments of Drivers to Parking Lots, with Nicole Tehari and Robert Shorten, IEEE Smart Cities, 2017.
- A Method for Fair Assignments of Drivers to Parking Lots, with Nicole Tehari and Robert Shorten, IEEE Smart Cities, 2017.
- Label Propagation for Mode Detection from Smartphone Data, with Mohsen Rezaei, Zachary Patterson, and Ali Yazdizadeh, 2017.
- On Charge Point Anxiety and the Sharing Economy, with Eoin Thompson et al., IEEE ITSC 2017.
- Joint energy demand prediction and control, with Mehdi Merai, AfricaTek 2017.
- Crowdsourced Electricity Demand Forecast, with Kenneth Humphreys, IEEE Smart Cities 2016.
- INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data, with Nikos Panagiotou et al., ECML-PKDD 2016
- Mining Hidden Constrained Streams in Practice: Informed Search in Dynamic Filter Spaces, with Nikos Panagiotou et al., ASONAM 2016.
- Distributionally Robust Optimisation in Congestion Control, with Jakub Marecek and Robert Shorten, ITS European Congress 2016.
- Pricing Vehicle Sharing with Proximity Information, with Jakub Marecek and Robert Shorten, IEEE Big Data and Smart City 2016
- Two-phase Q-learning for Bidding-based Vehicle Sharing, with Yinlam Chow and Marco Pavone, AAAI Spring Symposium 2016.
- Sensor Selection for Crowdsensing Dynamical Systems, with Francois Schnitzler and Shie Mannor, AISTATS 2015.
- Signaled Queueing, with Laura Brink and Robert Shorten, AAMAS 2015.
- Real-time Bidding-based Vehicle Sharing, with Yinlam Chow, AAMAS 2015.
- Asynchronous Algorithms for Network Utility Maximisation with a Single Bit, with Fabian Wirth, Sonja Stuedli, Martin Corless, and Robert Shorten, ECC 2015.
- A result for nonhomogeneous place-dependent Markov Chains arising in the study of the AIMD algorithm and its application to certain optimisation problems, with Fabian Wirth, Sonja Stuedli, Martin Corless, and Robert Shorten, Allerton 2014.
- Traffic Management using RTEC in OWL 2 RL, with Bernard Gorman and Jakub Marecek, ISWC 2014.
- Sample complexity of risk-averse bandit-arm selection, with Evdokia Nikolova, IJCAI 2013.
- Data-driven Distributionally Robust Polynomial Optimization, with Martin Mevissen and Emanuele Ragnoli, NIPS 2013.
- Minimizing risk measures in bandit problems, INFORMS APS 2013.
- Distributionally robust optimization for polynomial optimization problems, with Martin Mevissen and Emanuele Ragnoli, ISMP 2012.
- Mean Field Equilibria of Multiarmed Bandit Games, with Ramakrishna Gummadi, Ramesh Johari, EC 2012.
- Unimodal bandits, with Shie Mannor, ICML 2011.
- Lipschitz Bandits without the Lipschitz Constant, with Sebastien Bubeck and Gilles Stoltz, ALT 2011.
- Adaptive and Optimal Online Linear Regression on L1-balls, with Sebastien Gerchinovitz, ALT 2011.
- Arbitrarily Modulated Markov Decision Processes, with Shie Mannor, CDC 2009.
- Piecewise-stationary bandit problems with side observations, with Shie Mannor, ICML 2009.
- Online learning in Markov decision processes with arbitrarily changing rewards and transitions, with Shie Mannor, GameNets 2009.
- Markov decision processes with arbitrary reward processes, with Shie Mannor and Nahum Shimkin, EWRL 2008.
- Online learning with expert advice and finite-horizon constraints, with Branislav Kveton, Georgios Theocharous and Shie Mannor, AAAI 2008.
- A lazy approach to online learning with constraints, with Branislav Kveton, Georgios Theocharous and Shie Mannor, ISAIM 2008.
- Asymptotics of efficiency loss in competitive market mechanisms, with Shie Mannor, Infocom 2006.
Journal articles
- Ridesharing for emergency evacuation, with Joe Naoum-Sawaya, INFOR, 2017
- A Reinforcement Learning Technique for Optimizing Downlink Scheduling in an Energy-Limited Vehicular Network, with Ribal Atalah and Chadi Assi. IEEE Transactions on Vehicular Technology, 2016.
- r-Extreme Signalling for Congestion Control, with Jakub Marecek and Robert Shorten. International Journal of
Control, 2016.
- On the Design of Campus Parking Systems with QoS Guarantees, with Wynita Griggs, Fabian Wirth, Florian Hausler, and Robert Shorten. IEEE Transactions on Intelligent Transportation Systems, 2015.
- Signaling and obfuscation for congestion control, with Jakub Marecek and Robert Shorten. International Journal of Control [arXiv], 2015.
- Adaptive and Optimal Online Linear Regression on L1-balls, with Sebastien Gerchinovitz. Theoretical Computer Science, 2012.
- Markov decision processes with arbitrary reward processes, with Shie Mannor and Nahum Shimkin. Mathematics of Operations Research 34(3) [737-757], 2009.
- Online learning with sample path constraints, with Shie Mannor and John N. Tsitsiklis. Journal of Machine Learning Research 10(Mar):[569-590], 2009.
- Efficiency loss of market-based resource allocation with many participants, with Shie Mannor, IEEE Journal on Selected Areas in Communications 25(6), 1244-1259, 2007.
Students
PhD
Master's
Teaching
Privacy in Data Mining [Summer 2019].
Risk Analysis [Winter 2019].
Game Theory [Winter 2017], [Fall 2018].
Math for CS [Fall 2016].
Supply Chain Management [Winter 2016], [Fall 2017], [Fall 2018].
Supply Chain Design [Fall 2015], [Fall 2016], [Summer 2017], [Summer 2018].
Machine Learning [Spring 2014 and 2015].
Vita
CV