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Hoda Heidari
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2020 – today
- 2024
- [j6]Hoda Heidari, Zahra Einalou, Mehrdad Dadgostar, Hamidreza Hosseinzadeh, Leila Kalhor:
A Comparison of the Analysis of Methods for Feature Extraction and Classification in SSVEP BCIs. SN Comput. Sci. 5(4): 356 (2024) - [c36]Anna Kawakami
, Amanda Coston
, Haiyi Zhu
, Hoda Heidari
, Kenneth Holstein
:
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals. CHI 2024: 749:1-749:22 - [c35]Nari Johnson
, Sanika Moharana
, Christina N. Harrington
, Nazanin Andalibi
, Hoda Heidari
, Motahhare Eslami
:
The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment. FAccT 2024: 337-358 - [c34]Ningjing Tang
, Jiayin Zhi
, Tzu-Sheng Kuo
, Calla Kainaroi
, Jeremy J. Northup
, Kenneth Holstein
, Haiyi Zhu
, Hoda Heidari
, Hong Shen
:
AI Failure Cards: Understanding and Supporting Grassroots Efforts to Mitigate AI Failures in Homeless Services. FAccT 2024: 713-732 - [c33]Benjamin Laufer
, Jon M. Kleinberg
, Hoda Heidari
:
Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models. WWW 2024: 66-76 - [i33]Michael Feffer, Anusha Sinha, Zachary C. Lipton, Hoda Heidari:
Red-Teaming for Generative AI: Silver Bullet or Security Theater? CoRR abs/2401.15897 (2024) - [i32]Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein:
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder Early-stage Deliberations Around Public Sector AI Proposals. CoRR abs/2402.18774 (2024) - [i31]Nari Johnson, Sanika Moharana, Christina N. Harrington, Nazanin Andalibi, Hoda Heidari, Motahhare Eslami:
The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment. CoRR abs/2404.13802 (2024) - [i30]Anna Kawakami, Amanda Coston, Hoda Heidari, Kenneth Holstein, Haiyi Zhu:
Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use. CoRR abs/2405.12458 (2024) - [i29]Vijay Keswani, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong:
On the Pros and Cons of Active Learning for Moral Preference Elicitation. CoRR abs/2407.18889 (2024) - 2023
- [j5]Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar:
Perspectives on incorporating expert feedback into model updates. Patterns 4(7): 100780 (2023) - [c32]Violet Xinying Chen, Joshua Williams, Derek Leben, Hoda Heidari:
Local Justice and Machine Learning: Modeling and Inferring Dynamic Ethical Preferences toward Allocations. AAAI 2023: 5956-5964 - [c31]Michael Feffer, Hoda Heidari, Zachary C. Lipton:
Moral Machine or Tyranny of the Majority? AAAI 2023: 5974-5982 - [c30]Michael Feffer
, Michael Skirpan
, Zachary C. Lipton
, Hoda Heidari
:
From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research. AIES 2023: 38-48 - [c29]Michael Feffer
, Nikolas Martelaro
, Hoda Heidari
:
The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements. EAAMO 2023: 3:1-3:11 - [c28]Hoda Heidari
, Solon Barocas
, Jon M. Kleinberg
, Karen Levy
:
Informational Diversity and Affinity Bias in Team Growth Dynamics. EAAMO 2023: 18:1-18:10 - [c27]Emily Black
, Rakshit Naidu
, Rayid Ghani
, Kit T. Rodolfa
, Daniel E. Ho
, Hoda Heidari
:
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools. EAAMO 2023: 36:1-36:11 - [c26]Amanda Coston, Anna Kawakami, Haiyi Zhu
, Ken Holstein, Hoda Heidari:
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms. SaTML 2023: 690-704 - [i28]Hoda Heidari, Solon Barocas, Jon M. Kleinberg, Karen Levy
:
Informational Diversity and Affinity Bias in Team Growth Dynamics. CoRR abs/2301.12091 (2023) - [i27]Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein:
Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design. CoRR abs/2303.14602 (2023) - [i26]Michael Feffer, Hoda Heidari, Zachary C. Lipton:
Moral Machine or Tyranny of the Majority? CoRR abs/2305.17319 (2023) - [i25]Alex John London, Hoda Heidari:
Beneficent Intelligence: A Capability Approach to Modeling Benefit, Assistance, and Associated Moral Failures through AI Systems. CoRR abs/2308.00868 (2023) - [i24]Benjamin Laufer, Jon M. Kleinberg, Hoda Heidari:
Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models. CoRR abs/2308.04399 (2023) - [i23]Emily Black, Rakshit Naidu, Rayid Ghani, Kit T. Rodolfa, Daniel E. Ho, Hoda Heidari:
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools. CoRR abs/2309.17337 (2023) - [i22]Michael Feffer, Nikolas Martelaro, Hoda Heidari:
The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements. CoRR abs/2310.06269 (2023) - [i21]Mateo Dulce Rubio, Siqi Zeng, Qi Wang, Didier Alvarado, Francisco Moreno, Hoda Heidari, Fei Fang:
RELand: Risk Estimation of Landmines via Interpretable Invariant Risk Minimization. CoRR abs/2311.03115 (2023) - [i20]Nari Johnson, Hoda Heidari:
Assessing AI Impact Assessments: A Classroom Study. CoRR abs/2311.11193 (2023) - 2022
- [j4]Hoda Heidari, Solon Barocas, Jon M. Kleinberg, Karen Levy:
On modeling human perceptions of allocation policies with uncertain outcomes. SIGecom Exch. 20(1): 47-54 (2022) - [c25]Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon M. Kleinberg, Hoda Heidari:
Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects. FAccT 2022: 401-426 - [c24]Keegan Harris, Dung Daniel T. Ngo, Logan Stapleton, Hoda Heidari, Steven Wu:
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses. ICML 2022: 8502-8522 - [c23]Hoda Heidari, Jon M. Kleinberg:
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility (Extended Abstract). IJCAI 2022: 5289-5293 - [c22]Keegan Harris, Valerie Chen, Joon Sik Kim, Ameet Talwalkar, Hoda Heidari, Zhiwei Steven Wu:
Bayesian Persuasion for Algorithmic Recourse. NeurIPS 2022 - [i19]Nil-Jana Akpinar, Manish Nagireddy, Logan Stapleton, Hao Fei Cheng, Haiyi Zhu, Zhiwei Steven Wu, Hoda Heidari:
A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms. CoRR abs/2204.10233 (2022) - [i18]Charvi Rastogi, Liu Leqi, Kenneth Holstein, Hoda Heidari:
A Unifying Framework for Combining Complementary Strengths of Humans and ML toward Better Predictive Decision-Making. CoRR abs/2204.10806 (2022) - [i17]Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar:
Perspectives on Incorporating Expert Feedback into Model Updates. CoRR abs/2205.06905 (2022) - [i16]Benjamin Laufer, Sameer Jain, A. Feder Cooper, Jon M. Kleinberg, Hoda Heidari:
Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects. CoRR abs/2206.06738 (2022) - [i15]Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari:
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms. CoRR abs/2206.14983 (2022) - 2021
- [c21]Michele Loi, Anders Herlitz, Hoda Heidari:
Fair Equality of Chances for Prediction-based Decisions. AIES 2021: 756 - [c20]Mohammad Yaghini, Andreas Krause, Hoda Heidari:
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES 2021: 1023-1033 - [c19]Hoda Heidari, Jon M. Kleinberg:
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility. FAccT 2021: 15-25 - [c18]David Lindner, Hoda Heidari, Andreas Krause:
Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI 2021: 537-544 - [c17]Keegan Harris, Hoda Heidari, Zhiwei Steven Wu:
Stateful Strategic Regression. NeurIPS 2021: 28728-28741 - [c16]Hoda Heidari, Solon Barocas
, Jon M. Kleinberg, Karen Levy
:
On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes. EC 2021: 589-609 - [i14]Hoda Heidari, Jon M. Kleinberg:
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility. CoRR abs/2101.08451 (2021) - [i13]Hoda Heidari, Solon Barocas, Jon M. Kleinberg, Karen Levy:
On Modeling Human Perceptions of Allocation Policies with Uncertain Outcomes. CoRR abs/2103.05827 (2021) - [i12]David Lindner, Hoda Heidari, Andreas Krause:
Addressing the Long-term Impact of ML Decisions via Policy Regret. CoRR abs/2106.01325 (2021) - [i11]Keegan Harris, Hoda Heidari, Zhiwei Steven Wu:
Stateful Strategic Regression. CoRR abs/2106.03827 (2021) - [i10]Keegan Harris, Dung Daniel T. Ngo, Logan Stapleton, Hoda Heidari, Zhiwei Steven Wu:
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses. CoRR abs/2107.05762 (2021) - [i9]Keegan Harris, Valerie Chen, Joon Sik Kim, Ameet Talwalkar, Hoda Heidari, Zhiwei Steven Wu:
Bayesian Persuasion for Algorithmic Recourse. CoRR abs/2112.06283 (2021) - 2020
- [j3]Nuno Mota, Abhijnan Chakraborty, Asia J. Biega, Krishna P. Gummadi
, Hoda Heidari:
On the Desiderata for Online Altruism: Nudging for Equitable Donations. Proc. ACM Hum. Comput. Interact. 4(CSCW2): 126:1-126:21 (2020)
2010 – 2019
- 2019
- [j2]Sanjeev Goyal, Hoda Heidari, Michael J. Kearns:
Competitive contagion in networks. Games Econ. Behav. 113: 58-79 (2019) - [c15]Hoda Heidari, Michele Loi
, Krishna P. Gummadi
, Andreas Krause:
A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity. FAT 2019: 181-190 - [c14]Hoda Heidari, Vedant Nanda, Krishna P. Gummadi
:
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning. ICML 2019: 2692-2701 - [c13]Megha Srivastava, Hoda Heidari, Andreas Krause:
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. KDD 2019: 2459-2468 - [c12]Krishna P. Gummadi
, Hoda Heidari:
Economic Theories of Distributive Justice for Fair Machine Learning. WWW (Companion Volume) 2019: 1301-1302 - [c11]Abhijnan Chakraborty, Nuno Mota, Asia J. Biega, Krishna P. Gummadi
, Hoda Heidari:
On the Impact of Choice Architectures on Inequality in Online Donation Platforms. WWW 2019: 2623-2629 - [i8]Megha Srivastava, Hoda Heidari, Andreas Krause:
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. CoRR abs/1902.04783 (2019) - [i7]Hoda Heidari, Vedant Nanda, Krishna P. Gummadi:
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning. CoRR abs/1903.01209 (2019) - [i6]Mohammad Yaghini, Hoda Heidari, Andreas Krause:
A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness. CoRR abs/1911.03020 (2019) - 2018
- [j1]Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan:
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets. ACM Trans. Economics and Comput. 6(3-4): 15:1-15:26 (2018) - [c10]Hoda Heidari, Andreas Krause:
Preventing Disparate Treatment in Sequential Decision Making. IJCAI 2018: 2248-2254 - [c9]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca
, Krishna P. Gummadi
, Adish Singla
, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. KDD 2018: 2239-2248 - [c8]Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi
, Andreas Krause:
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. NeurIPS 2018: 1273-1283 - [i5]Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause:
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. CoRR abs/1806.04959 (2018) - [i4]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices. CoRR abs/1807.00787 (2018) - [i3]Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause:
A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity. CoRR abs/1809.03400 (2018) - 2017
- [i2]Hossein Azari, William D. Heavlin, Hoda Heidari, Max Lin, Sonia Todorova:
A General Framework for Evaluating Callout Mechanisms in Repeated Auctions. CoRR abs/1702.01803 (2017) - [i1]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
- [c7]Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod:
Pricing a Low-regret Seller. ICML 2016: 2559-2567 - [c6]Hoda Heidari, Michael J. Kearns, Aaron Roth:
Tight Policy Regret Bounds for Improving and Decaying Bandits. IJCAI 2016: 1562-1570 - 2015
- [c5]Hoda Heidari, Sébastien Lahaie, David M. Pennock, Jennifer Wortman Vaughan:
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets. EC 2015: 583-600 - 2014
- [c4]Moez Draief, Hoda Heidari, Michael J. Kearns:
New Models for Competitive Contagion. AAAI 2014: 637-644 - [c3]Kareem Amin, Hoda Heidari, Michael J. Kearns:
Learning from Contagion (Without Timestamps). ICML 2014: 1845-1853 - 2013
- [c2]Hoda Heidari, Michael J. Kearns:
Depth-Workload Tradeoffs for Workforce Organization. HCOMP 2013: 60-68 - 2011
- [c1]Zeinab Abbassi, Hoda Heidari:
Toward optimal vaccination strategies for probabilistic models. WWW (Companion Volume) 2011: 1-2
Coauthor Index
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last updated on 2024-08-25 19:15 CEST by the dblp team
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