Elisa’s Publications

PEER-REVIEWED CONFERENCES AND JOURNALS

• • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • Coordinate Descent with Bandit Sampling
      Farnood Salehi, Patrick Thiran and L. Elisa Celis
      Advances in Neural Information Processing Systems (NeurIPS), 2018
  • • 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
  • • 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
  • • Ranking with Fairness Constraints
      L. Elisa Celis, Damian Straszak and Nisheeth K. Vishnoi
      International Colloquium on Automata, Languages, and Programming (ICALP), 2018
  • • 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
  • • A Dynamics for Advertising on Networks
      L. Elisa Celis, Mina Dalirrooyfard and Nisheeth Vishnoi
      Conference on Web and Internet Economics (WINE), 2017
  • • 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
  • • 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
  • • Fair Personalization
      L. Elisa Celis and Nisheeth K. Vishnoi
      Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), 2017
  • • 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
  • • A Distributed Learning Dynamics in Social Groups
      L. Elisa Celis, Peter Krafft and Nisheeth Vishnoi
      ACM Symposium on Principles of Distributed Computing (PODC), 2017
  • • 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
  • • Auctions for Online Advertising with Constraints
      L. Elisa Celis, Farnood Salehi and Salman Salamatian
      Manufacturing & Service Operations Management Society Conference (MSOM), 2017
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • Lottery-based Payment Mechanism for Microtasks
      L. Elisa Celis, Shourya Roy and Vivek Mishra
      Conference on Human Computation & Crowdsourcing (HCOMP), WiP track, 2013
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • 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
  • • Local Dynamics in Exchange Networks via Random Turn Games
      L. Elisa Celis, Nikhil Devanur and Yuval Peres
      Workshop in Network Economics (WINE), 2010
  • • 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

•  

GRANTED PATENTS

• • • 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

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

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