Mobile EEG-Based Workers’ Stress Recognition by Applying Deep Neural Network H Jebelli, MM Khalili, SH Lee Advances in Informatics and Computing in Civil and Construction Engineering …, 2018 | 104 | 2018 |
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms X Zhang, MM Khalili, M Liu 35th International Conference on Machine Learning (ICML 2018), 2018 | 102 | 2018 |
A continuously updated, computationally efficient stress recognition framework using electroencephalogram (EEG) by applying online multitask learning algorithms (OMTL) H Jebelli, MM Khalili, SH Lee IEEE journal of biomedical and health informatics 23 (5), 1928-1939, 2018 | 86 | 2018 |
Designing cyber insurance policies: The role of pre-screening and security interdependence MM Khalili, P Naghizadeh, M Liu IEEE Transactions on Information Forensics and Security 13 (9), 2226-2239, 2018 | 76 | 2018 |
A Supervised Learning-Based Construction Workers’ Stress Recognition Using a Wearable Electroencephalography (EEG) Device H Jebelli, MM Khalili, S Hwang, SH Lee Construction Research Congress 2018, 40-50, 2018 | 74 | 2018 |
Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness X Zhang*, MM Khalili*, C Tekin Advances in Neural Information Processing Systems(*Equal Contribution …, 2019 | 67 | 2019 |
Embracing and controlling risk dependency in cyber-insurance policy underwriting MM Khalili, M Liu, S Romanosky Journal of Cybersecurity 5 (1), tyz010, 2019 | 35 | 2019 |
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms X Zhang, MM Khalili, M Liu 56th Annual Allerton Conference on Communication, Control, and Computing, 2018 | 32 | 2018 |
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms X Zhang, MM Khalili, M Liu IEEE Transactions on Information Forensics and Security (TIFS), 2019 | 29 | 2019 |
Designing cyber insurance policies: Mitigating moral hazard through security pre-screening MM Khalili, P Naghizadeh, M Liu International Conference on Game Theory for Networks, 63-73, 2017 | 28 | 2017 |
Improving Fairness and Privacy in Selection Problems MM Khalili, X Zhang, M Abroshan, S Sojoudi AAAI 2021, 2021 | 26 | 2021 |
Incentive design and market evolution of mobile user-provided networks MM Khalili, L Gao, J Huang, BH Khalaj 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS …, 2015 | 26 | 2015 |
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift G Aminian, M Abroshan, M Khalili, M Rodrigues, L Toni AISTATS, 2022 | 25 | 2022 |
Long-term impacts of fair machine learning X Zhang, MM Khalili, M Liu Ergonomics in Design 28 (3), 7-11, 2020 | 25 | 2020 |
Designing cyber insurance policies in the presence of security interdependence MM Khalili, P Naghizadeh, M Liu Proceedings of the 12th workshop on the Economics of Networks, Systems and …, 2017 | 23 | 2017 |
Embracing risk dependency in designing cyber-insurance contracts MM Khalili, P Naghizadeh, M Liu 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017 | 22 | 2017 |
Multi-level Assessment of Occupational Stress in the Field Using a Wearable EEG Headset H JEBELLI, M HABIBNEZHAD, MM KHALILI, MS FARDHOSSEINI | 21 | 2020 |
Fairness interventions as (dis) incentives for strategic manipulation X Zhang, MM Khalili, K Jin, P Naghizadeh, M Liu International Conference on Machine Learning, 26239-26264, 2022 | 17 | 2022 |
Contract Design for Purchasing Private Data Using a Biased Differentially Private Algorithm MM Khalili, X Zhang, M Liu The 14th Workshop on the Economics of Networks, Systems and Computation …, 2019 | 14 | 2019 |
Fair Sequential Selection Using Supervised Learning Models MM Khalili, X Zhang, M Abroshan NeurIPS 2021, 2021 | 13 | 2021 |