2018
Yang Liu and Yiling Chen
Surrogate Scoring Rules and Dominant Truth Serum. [Abstract]
arXiv, 2018.
Shuran Zheng, Bo Waggoner, Yang Liu and Yiling Chen
Active Information Acquisition for Linear Optimization
UAI 2018, to appear.
Chaowei Xiao, Armin Sarabi, Yang Liu , Bo Li, Mingyan Liu and Tudor Dumitras
From Patching Delays to Infection Symptoms: Using Risk
Profiles for an Early Discovery of Vulnerabilities Exploited
in the Wild
USENIX Security 2018, to appear.
Kaiqing Zhang, Yang Liu , Ji Liu, Tamer Başar and Mingyan Liu
Distributed Belief Averaging Using Seqeuntial Observations.
Automatica, accept provisionally as regular paper.
Yang Liu , Ji Liu and Tamer Başar
Gossip Gradient Descent. [Extended Abstract]
AAMAS 2018, Stockholm, Sweden.
Yang Liu and Chien-Ju Ho
Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning.
AAAI 2018, New Orleans, United States.
2017
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal and David Parkes
Calibrated Fairness in Bandits.
FATML 2017, Halifax, Canada.
CODE@MIT 2017, Cambridge, United States.
Yang Liu
Fair Optimal Stopping Policy for Sequential Matching.
UAI 2017, Sydney, Australia.
Yang Liu and Yiling Chen
Machine Learning aided Peer Prediction.
ACM EC 2017, Cambridge, United States
Yang Liu and Mingyan Liu
Crowd Learning: Improving Online Decision Making Using Crowdsourced Data.
IJCAI 2017, Melbourne, Australia.
Yang Liu and Yiling Chen
Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.
AAAI 2017, San Francisco, United States.
Ji Liu, Yang Liu, Angelia Nedich and Tamer Başar
An Approach to Distributed Parametric Learning with Streaming Data.
CDC 2017 (invited paper), Melbourne, Australia.
2016
Yang Liu and Yiling Chen
A Bandit Framework for Strategic Regression.
NIPS 2016, Barcelona, Spain.
Yang Liu and Yiling Chen
Learning to Incentivize: Eliciting Effort via Output Agreement.
IJCAI 2016, New York City, Uniteed States
Yang Liu and Mingyan Liu
Finding One's Best Crowd: Online Learning By Exploiting Source Similarity.
AAAI 2016, Phoenix, United States.
Wenwu He, James T. Kwok, Ji Zhu and Yang Liu
A Note on the Unification of Adaptive Online Learning
IEEE Trans. on Neural Networks and Learning Systems, 2016.
Yang Liu and Yining Wang
Doubly Active Learning: when Active Learning meets Active Crowdsourcing.
CrowdML'16 (NIPS'16), Barcelona, Spain.
Armin Sarabi, Parinaz Naghizadeh, Yang Liu and Mingyan Liu
Risky Business: Fine-grained Data Breach Prediction Using Business Profiles.
Journal of Cybersecurity, 2016.
Preliminary version appeared at WEIS 2015.
2015
Yang Liu and Mingyan Liu
An Online Learning Approach to Improving the Quality of Crowdsourcing.
ACM SIGMETRICS 2015, Portland, United States.
Extended version to appear at IEEE/ACM Transaction on Networkings, 2017.
Yang Liu, Armin Sarabi, Jing Zhang, Parinaz Ardabili, Manish Karir, Michael Bailey and Mingyan Liu
Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents.
USENIX Security 2015, Washington, D.C., United States.
Shang-Pin Sheng, Yang Liu and Mingyan Liu
A Regulated Oligopoly Multi-Market Model for Trading Smart Data.
IEEE SDP 2015, in conjunction with IEEE INFOCOM 2015, Hong Kong, China.
Yang Liu and Mingyan Liu
An Online Approach to Dynamic Channel Access and Transmission Scheduling.
ACM MobiHoc 2015, Hangzhou, China.
Extended version to appear at Handbook of Cognitive Radio, Springer.
2014
Yang Liu and Mingyan Liu
Detecting Hidden Propagation Structure and Its Application to Analyzing Phishing.
ACM/IEEE DSAA 2014, best application paper award, Shanghai, China.
Yang Liu, Mingyan Liu and Sahand Haji Ali Ahmad
Sufficient Conditions on Optimality of Myopic Sensing in Opportunistic Channel Access: A Unifying Framework.
IEEE Transaction on Information Theory, 2014.
Other and older publications on "decision making in networks":
Yang Liu*, Yi Ouyang* and Mingyan Liu
Optimal Relay Selection with Non-negligible Probing Time.
IEEE ICC 2015, London, United Kingdom. * indicates equal contribution.
Yang Liu and Mingyan Liu
To Stay Or To Switch: Multiuser Dynamic Channel Access.
IEEE INFOCOM 2013, Turin, Italy.
Extended version appeared at IEEE Transaction on Mobile Computing, 2014.
Yang Liu, Mingyan Liu and Jing Deng
Is Diversity Gain Worth the Pain:a Delay Comparison between Opportunistic Multi-channel MAC and Single-channel MAC.
IEEE INFOCOM 2012, Orlando, United States.
Extended version appeared at IEEE Journal on Selected Areas in Communications, 2013.