PEER-REVIEWED CONFERENCES AND JOURNALS
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Public attitudes value interpretability but prioritize accuracy in Artificial Intelligence
AnneMarie Nussberger, Lan Luo, L. Elisa Celis, Molly J. Crockett
Nature Communications 13, 5821, 2022 -
Diverse Representation via Computational Participatory Elections – Lessons from a Case Study
Florian Evéquoz, Johan Rochel, Vijay Keswani, L. Elisa Celis
ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022 - Revisiting Group Fairness Metrics: The Effect of Networks
Anay Mehrotra, Jeffrey Sachs, and L. Elisa Celis
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2022 -
Fair Classification with Adversarial Perturbations
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
Advances in Neural Information Processing Systems (NeurIPS), 2021 -
Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees
L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi
International Conference on Machine Learning (ICML), 2021 -
Auditing for Diversity using Representative Examples
Vijay Keswani, L. Elisa Celis
ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD), 2021 - Dialect Diversity in Text Summarization on Twitter
Vijay Keswani, L. Elisa Celis
The Web Conference (WWW), 2021 - Mitigating Bias in Set Selection with Noisy Protected Attributes
Anay Mehrotra, L. Elisa Celis
Fairness Accountability and Transparency Conference (FAccT), 2021 - The Effect of the Rooney Rule on Implicit Bias in the Long Term
L. Elisa Celis, Chris Hays, Anay Mehrotra, Nisheeth K. Vishnoi
Fairness Accountability and Transparency Conference (FAccT), 2021 - Implicit Diversity in Image Summarization
L. Elisa Celis, Vijay Keswani
Computer-Supported Cooperative Work and Social Computing (CSCW), 2020 - Data Preprocessing to Mitigate Bias: A Maximum Entropy-based Approach
L. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi
International Conference on Machine Learning (ICML), 2020 [blogpost] - Towards Just, Fair and Interpretable Methods for Judicial Subset Selection
Lingxiao Huang, Julia Wei, L. Elisa Celis
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 2020 - Interventions for Ranking in the Presence of Implicit Bias
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
Fairness Accountability and Transparency Conference (FAccT), 2020 - Assessing Social and Intersectional Biases in Contextualized Word Representations
Yi Chern Tan and L. Elisa Celis
Advances in Neural Information Processing Systems (NeurIPS), 2019
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- Toward Controlling Discrimination in Online Advertising
L. Elisa Celis, Anay Mehrotra and Nisheeth Vishnoi
International Conference on Machine Learning (ICML), 2019
Oral presentation and BEST STUDENT PAPER at MD4SG, 2019
Accepted at the Stony Brook International Conference on Game Theory (GTCenter), 2019
- Toward Controlling Discrimination in Online Advertising
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- A General Framework for Sensor Placement in Source Localization
Brunella Spinelli, L. Elisa Celis and Patrick Thiran
IEEE Transactions on Network Science and Engineering, 2019
- A General Framework for Sensor Placement in Source Localization
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- Controlling Polarization in Personalization: An Algorithmic Framework
L. Elisa Celis, Sayash Kapoor, Farnood Salehi and Nisheeth K. Vishnoi
Fairness Accountability and Transparency Conference (FAT*), 2019
BEST PAPER AWARD
- Controlling Polarization in Personalization: An Algorithmic Framework
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- Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
L. Elisa Celis, Lingxiao Huang, Vijay Keswani and Nisheeth Vishnoi
Fairness Accountability and Transparency Conference (FAT*), 2019
- Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
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- Balanced News Using Constrained Bandit-based Personalization
Sayash Kapoor, Vijay Keswani, Nisheeth Vishnoi and L. Elisa Celis
International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI), 2018
Invited Paper to AI Communications, volume 32, issue 1, 2019
- Balanced News Using Constrained Bandit-based Personalization
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- Multiwinner Voting with Fairness Constraints
L. Elisa Celis, Lingxiao Huang and Nisheeth Vishnoi
International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI), 2018
- Multiwinner Voting with Fairness Constraints
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- Coordinate Descent with Bandit Sampling
Farnood Salehi, Patrick Thiran and L. Elisa Celis
Advances in Neural Information Processing Systems (NeurIPS), 2018
- Coordinate Descent with Bandit Sampling
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- Fair and Diverse DPP-based Data Summarization
L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria and Nisheeth K. Vishnoi
International Conference on Machine Learning (ICML), 2018
- Fair and Diverse DPP-based Data Summarization
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- How Many Sensors to Localize the Source? The Double Metric Dimension of Random Networks
Brunella Spinelli, L. Elisa Celis and Patrick Thiran:
Allerton 2018: 1036-1043
- How Many Sensors to Localize the Source? The Double Metric Dimension of Random Networks
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- Ranking with Fairness Constraints
L. Elisa Celis, Damian Straszak and Nisheeth K. Vishnoi
International Colloquium on Automata, Languages, and Programming (ICALP), 2018
- Ranking with Fairness Constraints
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- The Effect of Transmission Variance on Observer Placement for Source-Localization
Brunella Spinelli, L. Elisa Celis and Patrick Thiran
Journal of Applied Network Science, 2017
- The Effect of Transmission Variance on Observer Placement for Source-Localization
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- A Dynamics for Advertising on Networks
L. Elisa Celis, Mina Dalirrooyfard and Nisheeth Vishnoi
Conference on Web and Internet Economics (WINE), 2017
- A Dynamics for Advertising on Networks
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- A Model for Social Network Formation: Efficiency, Stability and Dynamics
L. Elisa Celis and Aida Mousavifar
Accepted at the Stony Brook International Conference on Game Theory (GTCenter), 2016
Poster presentation at the Conference on Web and Internet Economics (WINE), 2017
- A Model for Social Network Formation: Efficiency, Stability and Dynamics
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- On the Complexity of Constrained Determinantal Point Processes
L. Elisa Celis, Amit Deshpande, Tarun Kathuria, Damian Straszak and Nisheeth K. Vishnoi
International Workshop on Randomization and Computation (RANDOM), 2017
- On the Complexity of Constrained Determinantal Point Processes
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- Fair Personalization
L. Elisa Celis and Nisheeth K. Vishnoi
Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), 2017
- Fair Personalization
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- Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad, Farnood Salehi, L. Elisa Celis, Patrick Thiran and Michael Unser
International Conference on Machine Learning (ICML), 2017
- Dictionary Learning Based on Sparse Distribution Tomography
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- A Distributed Learning Dynamics in Social Groups
L. Elisa Celis, Peter Krafft and Nisheeth Vishnoi
ACM Symposium on Principles of Distributed Computing (PODC), 2017
- A Distributed Learning Dynamics in Social Groups
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- What Do Users Want in Q&A Sites: Quality or Diversity?
L. Elisa Celis and Siddhartha Tekriwal
International Conference on Computational Social Science (IC2S2), 2017
- What Do Users Want in Q&A Sites: Quality or Diversity?
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- Auctions for Online Advertising with Constraints
L. Elisa Celis, Farnood Salehi and Salman Salamatian
Manufacturing & Service Operations Management Society Conference (MSOM), 2017
- Auctions for Online Advertising with Constraints
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- Back to the source: An online approach for sensor placement and source localization
Brunella Spinelli, L. Elisa Celis and Patrick Thiran
World Wide Web Conference (WWW), 2017
- Back to the source: An online approach for sensor placement and source localization
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- How to be Fair and Diverse?
L. Elisa Celis, Amit Deshpande, Tarun Kathuria and Nisheeth Vishnoi
Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), 2016
- How to be Fair and Diverse?
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- Observer Placement for Source Localization: The Effect of Budgets and Transmission Variance
Brunella Spinelli, L. Elisa Celis and Patrick Thiran
Annual Allerton Conference on Communication, Control and Computing (Allerton), 2016
Presented at the International Workshop on Complex Networks and their Applications (ComplexNets), 2016
- Observer Placement for Source Localization: The Effect of Budgets and Transmission Variance
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- Sequential Voting Promotes Collective Discovery in Social Recommendation Systems
L. Elisa Celis, Peter M. Krafft, and Nathan Kobe
International AAAI Conference on Web and Social Media (ICWSM), 2016
- Sequential Voting Promotes Collective Discovery in Social Recommendation Systems
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- Assignment Techniques for Crowdsourcing Sensitive Tasks
L. Elisa Celis, Sai Praneeth Reddy, Ishaan Preet Singh and Shailesh Vaya
Computer-Supported Cooperative Work and Social Computing (CSCW), 2016
- Assignment Techniques for Crowdsourcing Sensitive Tasks
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- Crowds of Crowds: Performance based Modeling and Optimization over Multiple Crowdsourcing Platforms
Sakyajit Bhattacharya, Elisa Celis, Deepthi Chander, Koustuv Dasgupta, Saraschandra Karanam, and Vaibhav Rajan
Human Computation Journal, 2015
- Crowds of Crowds: Performance based Modeling and Optimization over Multiple Crowdsourcing Platforms
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- Budgeted Sensor Placement for Source Localization on Trees
L. Elisa Celis, Filip Pavetic, Brunella Spinelli and Patrick Thiran
Algorithms, Graphs and Optimization Symposium (LAGOS), 2015
- Budgeted Sensor Placement for Source Localization on Trees
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- Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions
L. Elisa Celis, Greg Lewis, Markus Mobius and Hamid Nazerzadeh
Management Science, 2014
- Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions
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- Adaptive Performance Optimization over Crowd Labor Channels
Saras Karanam, L. Elisa Celis, Deepthi Chander, Koustuv Dasgupta and Vaibhav Rajan
Conference on Human Computation & Crowdsourcing (HCOMP), WiP track, 2014
- Adaptive Performance Optimization over Crowd Labor Channels
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- Post it or Not: Viewership Based Posting of Crowdsourced Tasks
Pallavi Manohar, Deepthi Chander, L. Elisa Celis, Koustuv Dasgupta, and Sakyajit Bhattacharya
Conference on Human Computation & Crowdsourcing (HCOMP), WiP track, 2014
- Post it or Not: Viewership Based Posting of Crowdsourced Tasks
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- CrowdControl: An online learning approach for optimal task scheduling in a dynamic crowd platform
Vaibhav Rajan, Sakyajit Bhattacharya, L. Elisa Celis, Deepthi Chander, Koustuv Dasgupta and Saras Karanam
ML meets Crowdsourcing Workshop at the Int. Conf. on Machine Learning (ICML), 2013
- CrowdControl: An online learning approach for optimal task scheduling in a dynamic crowd platform
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- Balls and Bins: Smaller Hash Families and Faster Evaluation
L. Elisa Celis, Omer Reingold, Gil Segev and Udi Wieder
SIAM Journal on Computing (SICOMP), 2013
- Balls and Bins: Smaller Hash Families and Faster Evaluation
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- Lottery-based Payment Mechanism for Microtasks
L. Elisa Celis, Shourya Roy and Vivek Mishra
Conference on Human Computation & Crowdsourcing (HCOMP), WiP track, 2013
- Lottery-based Payment Mechanism for Microtasks
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- On Revenue Maximization for Agents with Costly Information Acquisition
L. Elisa Celis, Dimitrios Gklezakos and Anna Karlin
International Colloquium on Automata, Languages and Programming, (ICALP), 2013
- On Revenue Maximization for Agents with Costly Information Acquisition
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- Adaptive Crowdsourcing for Temporal Crowds
L. Elisa Celis, Koustuv Dasgupta and Vaibhav Rajan
Temporal Web Analytics Workshop at the Int. World Wide Web Conf. (WWW), 2013
- Adaptive Crowdsourcing for Temporal Crowds
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- Approximately Revenue-Maximizing Mechanisms for Deliberative Agents
L. Elisa Celis, Anna Karlin, Kevin Leyton-Brown, Thach Nguyen and David Thompson
Association for the Advancement of Artificial Intelligence (AAAI), 2012
- Approximately Revenue-Maximizing Mechanisms for Deliberative Agents
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- Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions
L. Elisa Celis, Greg Lewis, Markus Mobius and Hamid Nazerzadeh
Manufacturing & Service Operations Management Society Conference (MSOM), 2012
- Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions
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- Balls and Bins: Smaller Hash Families and Faster Evaluation
L. Elisa Celis, Omer Reingold, Gil Segev and Udi Wieder
Foundations of Computer Science (FOCS), 2011
- Balls and Bins: Smaller Hash Families and Faster Evaluation
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- Buy-it-Now or Take-a-Chance: A Simple Sequential Screening Mechanism
L. Elisa Celis, Gregory Lewis, Markus Mobius and Hamid Nazerzadeh
International World Wide Web Conference (WWW), 2011
- Buy-it-Now or Take-a-Chance: A Simple Sequential Screening Mechanism
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- Local Dynamics in Exchange Networks via Random Turn Games
L. Elisa Celis, Nikhil Devanur and Yuval Peres
Workshop in Network Economics (WINE), 2010
- Local Dynamics in Exchange Networks via Random Turn Games
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- Convergence of Local Dynamics to Balanced Outcomes in Exchange Networks
Yossi Azar, Benjamin Birnbaum, L. Elisa Celis, Nikhil Devanur and Yuval Peres
Foundations of Computer Science (FOCS), 2009 - Traffic Grooming for Single Source Multicast Communication in WDM Rings
Dave Buchfuhrer, Timothy Carnes, L. Elisa Celis, Brian Tagiku and Ran Libeskind-Hadas
International Conference on Communications (ICC), 2005
- Convergence of Local Dynamics to Balanced Outcomes in Exchange Networks
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GRANTED PATENTS
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- Method and system for recommending tasks to crowdworker
Chithra Balamurugan, L. Elisa Celis, Koustuv Dasgupta and Saras Karanam
Oct 2015. Patent No: US9152919 B2 - Method and system for managing allocation of tasks to be crowdsourced
L. Elisa Celis and Koustuv Dasgupta
Aug 2015. Patent No: US9098343 B2
- Method and system for recommending tasks to crowdworker
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MANUSCRIPTS
- Improved Adversarial Learning for Fair Classification
L. Elisa Celis and Vijay Keswani
arXiv:1901.10443
- Stochastic Optimization with Bandit Sampling
Farnood Salehi, Patrick Thiran and L. Elisa Celis
arXiv:1708.02544
- Learn From Thy Neighbor: Stochastic and Adversarial Bandits in a Network
L. Elisa Celis and Farnood Salehi
Presented at the International Symposium on Mathematical Programming (ISMP), 2015
arXiv:1704.04470
- Improved Adversarial Learning for Fair Classification