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ORCIDShahin Jabbari
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2020 – today
- 2024
[j2]Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju:
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. Trans. Mach. Learn. Res. 2024 (2024)- [c17]David Gefen, Shahin Jabbari, Rezvaneh (Shadi) Rezapour, Aria Pessianzadeh, Kshitij Kayastha, Hilde Van den Bulck:
The Evolving Meaning of Trust and Risk in Reddit Discourse about ChatGPT. AMCIS 2024 - [i17]Kshitij Kayastha, Vasilis Gkatzelis, Shahin Jabbari:
Learning-Augmented Robust Algorithmic Recourse. CoRR abs/2410.01580 (2024) - 2023
- [c16]Robert C. Gray
, Jennifer Villareale, Thomas Boyd Fox, Diane H. Dallal, Santiago Ontañón, Danielle Arigo, Shahin Jabbari, Jichen Zhu:
Improving Fairness in Adaptive Social Exergames via Shapley Bandits. IUI 2023: 322-336 - [i16]Robert C. Gray, Jennifer Villareale, Thomas B. Fox, Diane H. Dallal, Santiago Ontañón, Danielle Arigo, Shahin Jabbari, Jichen Zhu:
Improving Fairness in Adaptive Social Exergames via Shapley Bandits. CoRR abs/2302.09298 (2023) - 2022
- [j1]Palvi Aggarwal, Omkar Thakoor, Shahin Jabbari, Edward A. Cranford, Christian Lebiere, Milind Tambe, Cleotilde Gonzalez:
Designing effective masking strategies for cyberdefense through human experimentation and cognitive models. Comput. Secur. 117: 102671 (2022) - [c15]Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik:
Solving structured hierarchical games using differential backward induction. UAI 2022: 1107-1117 - [i15]Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, Himabindu Lakkaraju:
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective. CoRR abs/2202.01602 (2022) - [i14]Vivek Khimani, Shahin Jabbari:
TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments. CoRR abs/2211.00735 (2022) - 2021
- [c14]Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe:
Fair Influence Maximization: a Welfare Optimization Approach. AAAI 2021: 11630-11638 - [c13]Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe:
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. AAMAS 2021: 992-1000 - [c12]Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, Himabindu Lakkaraju:
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. ICML 2021: 110-119 - [i13]Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe:
Active Screening for Recurrent Diseases: A Reinforcement Learning Approach. CoRR abs/2101.02766 (2021) - [i12]Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju:
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations. CoRR abs/2102.10618 (2021) - [i11]Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael P. Wellman, Yevgeniy Vorobeychik:
A Game-Theoretic Approach for Hierarchical Policy-Making. CoRR abs/2102.10646 (2021) - [i10]Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik:
Solving Structured Hierarchical Games Using Differential Backward Induction. CoRR abs/2106.04663 (2021) - 2020
- [c11]Ankit Bhardwaj, Han-Ching Ou, Haipeng Chen, Shahin Jabbari, Milind Tambe, Rahul Panicker, Alpan Raval:
Robust Lock-Down Optimization for COVID-19 Policy Guidance. AI4SG@AAAI Fall Symposium 2020 - [c10]Omkar Thakoor, Shahin Jabbari, Palvi Aggarwal, Cleotilde Gonzalez, Milind Tambe, Phebe Vayanos:
Exploiting Bounded Rationality in Risk-Based Cyber Camouflage Games. GameSec 2020: 103-124 - [i9]Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Eric Rice, Milind Tambe:
Fair Influence Maximization: A Welfare Optimization Approach. CoRR abs/2006.07906 (2020)
2010 – 2019
- 2019
- [c9]Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman:
Fair Algorithms for Learning in Allocation Problems. FAT 2019: 170-179 - [c8]Yu Chen, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern:
Network Formation under Random Attack and Probabilistic Spread. IJCAI 2019: 180-186 - [c7]Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael J. Kearns, Zachary Schutzman:
Equilibrium Characterization for Data Acquisition Games. IJCAI 2019: 252-258 - [i8]Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael J. Kearns, Zachary Schutzman:
Equilibrium Characterization for Data Acquisition Games. CoRR abs/1905.08909 (2019) - [i7]Yu Chen, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern:
Network Formation under Random Attack and Probabilistic Spread. CoRR abs/1906.00241 (2019) - 2018
- [i6]Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman:
Fair Algorithms for Learning in Allocation Problems. CoRR abs/1808.10549 (2018) - 2017
- [c6]Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Aaron Roth:
Fairness in Reinforcement Learning. ICML 2017: 1617-1626 - [i5]Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel, Aaron Roth:
A Convex Framework for Fair Regression. CoRR abs/1706.02409 (2017) - 2016
- [c5]Shahin Jabbari, Ryan M. Rogers, Aaron Roth, Zhiwei Steven Wu:
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs. NIPS 2016: 1570-1578 - [c4]Sanjeev Goyal, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern:
Strategic Network Formation with Attack and Immunization. WINE 2016: 429-443 - [i4]Shahin Jabbari, Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Aaron Roth:
Fair Learning in Markovian Environments. CoRR abs/1611.03071 (2016) - 2015
- [c3]Sepehr Assadi, Justin Hsu, Shahin Jabbari:
Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets. HCOMP 2015: 12-21 - [i3]Shahin Jabbari, Ryan M. Rogers, Aaron Roth, Zhiwei Steven Wu:
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs. CoRR abs/1506.02162 (2015) - [i2]Sepehr Assadi, Justin Hsu, Shahin Jabbari:
Online Assignment of Heterogeneous Tasks in Crowdsourcing Markets. CoRR abs/1508.03593 (2015) - [i1]Sanjeev Goyal, Shahin Jabbari, Michael J. Kearns, Sanjeev Khanna, Jamie Morgenstern:
Strategic Network Formation with Attack and Immunization. CoRR abs/1511.05196 (2015) - 2013
- [c2]Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan:
Adaptive Task Assignment for Crowdsourced Classification. ICML (1) 2013: 534-542 - 2012
- [c1]Shahin Jabbari, Robert C. Holte, Sandra Zilles:
PAC-Learning with General Class Noise Models. KI 2012: 73-84
Coauthor Index
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last updated on 2024-11-11 21:28 CET by the dblp team
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