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Amélie Marian
Amélie Marian
Department of Computer Science
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Category: Conferences

Conferences

December 2023: “Explainable disparity compensation for efficient fair ranking,” With Abraham Gale accepted for publication at ICDE’24

Our paper on using bonus points to make ranking results more diverse and fair: “Explainable disparity compensation for efficient fair ranking,” was accepted at ICDE’24

Conferences

April 2023: “Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery” accepted for publication at FAccT’23

My paper: “Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery” was accepted at FAccT’23

Conferences

December 2022: “One of Us: a Multiplayer Web-based Game for Digital Evidence Acquisition of Scripts through Crowdsourcing,” by Varvara Kalokyri, Alexander Borgida, and Amélie Marian” accepted at CHIIR’23

Our paper:  “One of Us: a Multiplayer Web-based Game for Digital Evidence Acquisition of Scripts through Crowdsourcing,” by Varvara Kalokyri, Alexander Borgida, and Amélie Marian was accepted at CHIIR’23

Conferences

August 2022: “Identifying Possible Winners in Ranked Choice Voting Elections with Outstanding Ballots,” by Alborz Jelvani and Amélie Marian” accepted at HCOMP’22

Our paper:  “Identifying Possible Winners in Ranked Choice Voting Elections with Outstanding Ballots,” by Alborz Jelvani and Amélie Marian was accepted at HCOMP’22

Conferences

June 2022: “Fairness-aware federated matrix factorization,” by Schuchang Liu, Yingqiang Ge, Shuyuan Xu, Yongfeng Zhang, and Amélie Marian” accepted at RecSys’22

Our paper:  “Fairness-aware federated matrix factorization,” by Schuchang Liu, Yingqiang Ge, Shuyuan Xu, Yongfeng Zhang, and Amélie Marian was accepted at RecSys’22

Conferences

September 2021: “A Frequency-Based Learning-To-Rank Approach for Personal Digital Traces,” with Daniela Vianna, accepted for publication at HiCSS’22

Our paper on searching personal data:  “A Frequency-Based Learning-To-Rank Approach for Personal Digital Traces” was accepted at HiCSS’22

Conferences

July 2021: “Supporting Human Memory by Reconstructing Personal Episodic Narratives from Digital Traces,” with Valia Kalokyri and Alex Borgida, is accepted for publication at ICWSM 2022

Our paper on understanding and linking personal data traces: “Supporting Human Memory by Reconstructing Personal Episodic Narratives from Digital Traces,” with Valia Kalokyri and Alex Borgida, was accepted for publication …

Conferences

April 2021: “FedCT: Federated Collaborative Transfer for Recommendation,” by Shuchang Liu, Shuyuan Xu, Wenhui Yu, Zuohui Fu, Yongfeng Zhang  and Amélie Marian has been accepted for presentation at SIGIR’21

Conferences

December 2020: “Explaining Monotonic Ranking Functions,” with Abraham Gale was published in PVLDB, 14(4), 2020

Conferences

June 2019: Our Paper on “Metrics for Explainable Ranking Functions,” with Abraham Gale was accepted in the EARS SIGIR 2019 workshop

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