Michael D. Ekstrand

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 81

Top Topics

Query Reformulation

Information Retrieval

Lessons Learned

Top Venues

UMAP (Adjunct Publication)

Publications

Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloé Bakalar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Xian Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. Trans. Recomm. Syst. 2 (3) (2024)
Jacy Reese Anthis, Kristian Lum, Michael D. Ekstrand, Avi Feller, Alexander D'Amour, Chenhao Tan
The Impossibility of Fair LLMs. CoRR (2024)
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
Distributionally-Informed Recommender System Evaluation. Trans. Recomm. Syst. 2 (1) (2024)
Amifa Raj, Michael D. Ekstrand
Towards Optimizing Ranking in Grid-Layout for Provider-Side Fairness. ECIR (5) (2024)
Michael D. Ekstrand, Lex Beattie, Maria Soledad Pera, Henriette Cramer
Not Just Algorithms: Strategically Addressing Consumer Impacts in Information Retrieval. ECIR (4) (2024)
Ngozi Ihemelandu, Michael D. Ekstrand
Multiple Testing for IR and Recommendation System Experiments. ECIR (3) (2024)
Christine Pinney, Amifa Raj, Alex Hanna, Michael D. Ekstrand
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access. CHIIR (2023)
Amifa Raj, Michael D. Ekstrand
Unified Browsing Models for Linear and Grid Layouts. CoRR (2023)
Ngozi Ihemelandu, Michael D. Ekstrand
Inference at Scale Significance Testing for Large Search and Recommendation Experiments. CoRR (2023)
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
Distributionally-Informed Recommender System Evaluation. CoRR (2023)
Michael D. Ekstrand, Maria Soledad Pera, Katherine Landau Wright
Seeking Information with a More Knowledgeable Other. Interactions 30 (1) (2023)
Alexandra Olteanu, Michael D. Ekstrand, Carlos Castillo, Jina Suh
Responsible AI Research Needs Impact Statements Too. CoRR (2023)
Ngozi Ihemelandu, Michael D. Ekstrand
Inference at Scale: Significance Testing for Large Search and Recommendation Experiments. SIGIR (2023)
Michael D. Ekstrand, Jean Garcia-Gathright, Nasim Sonboli, Amifa Raj, Karlijn Dinnissen
FAccTRec 2023: The 6th Workshop on Responsible Recommendation. RecSys (2023)
Ngozi Ihemelandu, Michael D. Ekstrand
Candidate Set Sampling for Evaluating Top-N Recommendation. CoRR (2023)
Ngozi Ihemelandu, Michael D. Ekstrand
Candidate Set Sampling for Evaluating Top-N Recommendation. WI/IAT (2023)
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac Johnson
Overview of the TREC 2022 Fair Ranking Track. CoRR (2023)
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac L. Johnson
Overview of the TREC 2021 Fair Ranking Track. CoRR (2023)
Amifa Raj, Bhaskar Mitra, Nick Craswell, Michael D. Ekstrand
Patterns of Gender-Specializing Query Reformulation. SIGIR (2023)
Amifa Raj, Bhaskar Mitra, Nick Craswell, Michael D. Ekstrand
Patterns of gender-specializing query reformulation. CoRR (2023)
Amifa Raj, Michael D. Ekstrand
Towards Measuring Fairness in Grid Layout in Recommender Systems. CoRR (2023)
Christine Pinney, Amifa Raj, Alex Hanna, Michael D. Ekstrand
Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access. CoRR (2023)
Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
Fairness in Information Access Systems. Found. Trends Inf. Retr. 16 (1-2) (2022)
Michael D. Ekstrand, Graham McDonald, Amifa Raj, Isaac Johnson
Overview of the TREC 2022 Fair Ranking Track. TREC (2022)
Amifa Raj, Michael D. Ekstrand
Measuring Fairness in Ranked Results: An Analytical and Empirical Comparison. SIGIR (2022)
Amifa Raj, Michael D. Ekstrand
Fire Dragon and Unicorn Princess; Gender Stereotypes and Children's Products in Search Engine Responses. CoRR (2022)
Michael D. Ekstrand, Maria Soledad Pera
Matching Consumer Fairness Objectives & Strategies for RecSys. CoRR (2022)
Nasim Sonboli, Robin Burke, Michael D. Ekstrand, Rishabh Mehrotra
The Multisided Complexity of Fairness in Recommender Systems. AI Mag. 43 (2) (2022)
Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. CoRR (2022)
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sergey Feldman, Sebastian Kohlmeier
Overview of the TREC 2020 Fair Ranking Track. CoRR (2021)
Michael D. Ekstrand, Daniel Kluver
Exploring author gender in book rating and recommendation. User Model. User Adapt. Interact. 31 (3) (2021)
Amifa Raj, Ashlee Milton, Michael D. Ekstrand
Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations. CoRR (2021)
Ömer Kirnap, Fernando Diaz, Asia Biega, Michael D. Ekstrand, Ben Carterette, Emine Yilmaz
Estimation of Fair Ranking Metrics with Incomplete Judgments. WWW (2021)
Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom
SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research. RecSys (2021)
A. K. M. Nuhil Mehdy, Michael D. Ekstrand, Bart P. Knijnenburg, Hoda Mehrpouyan
Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans. CoRR (2021)
Ngozi Ihemelandu, Michael D. Ekstrand
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse. Perspectives@RecSys (2021)
Robin Burke, Michael D. Ekstrand, Nava Tintarev, Julita Vassileva
Preface to the special issue on fair, accountable, and transparent recommender systems. User Model. User Adapt. Interact. 31 (3) (2021)
Lawrence Spear, Ashlee Milton, Garrett Allen, Amifa Raj, Michael Green, Michael D. Ekstrand, Maria Soledad Pera
Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior. RecSys (2021)
Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
Fairness and Discrimination in Information Access Systems. CoRR (2021)
Ömer Kirnap, Fernando Diaz, Asia Biega, Michael D. Ekstrand, Ben Carterette, Emine Yilmaz
Estimation of Fair Ranking Metrics with Incomplete Judgments. CoRR (2021)
A. K. M. Nuhil Mehdy, Michael D. Ekstrand, Bart P. Knijnenburg, Hoda Mehrpouyan
Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans. UMAP (2021)
Michael D. Ekstrand, Amifa Raj, Graham McDonald, Isaac Johnson
Overview of the TREC 2021 Fair Ranking Track. TREC (2021)
Michael D. Ekstrand, Pierre-Nicolas Schwab, Toshihiro Kamishima, Nasim Sonboli
FAccTRec 2021: The 4th Workshop on Responsible Recommendation. RecSys (2021)
Ngozi Ihemelandu, Michael D. Ekstrand
Statistical Inference: The Missing Piece of RecSys Experiment Reliability Discourse. CoRR (2021)
Michael D. Ekstrand
Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation. CoRR (2021)
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, Ben Carterette
Evaluating Stochastic Rankings with Expected Exposure. CIKM (2020)
Mucun Tian, Michael D. Ekstrand
Estimating Error and Bias in Offline Evaluation Results. CHIIR (2020)
Bamshad Mobasher, Styliani Kleanthous, Bettina Berendt, Michael D. Ekstrand, Jahna Otterbacher, Avital Shulner Tal
UMAP 2020 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2020) Chairs' Welcome. UMAP (Adjunct Publication) (2020)
Michael D. Ekstrand, Katherine Landau Wright, Maria Soledad Pera
Enhancing classroom instruction with online news. Aslib J. Inf. Manag. 72 (5) (2020)
Michael D. Ekstrand, Pierre-Nicolas Schwab, Jean Garcia-Gathright, Toshihiro Kamishima, Nasim Sonboli
3rd FAccTRec Workshop: Responsible Recommendation. RecSys (2020)
Mucun Tian, Michael D. Ekstrand
Estimating Error and Bias in Offline Evaluation Results. CoRR (2020)
Amifa Raj, Connor Wood, Ananda Montoly, Michael D. Ekstrand
Comparing Fair Ranking Metrics. CoRR (2020)
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sebastian Kohlmeier
Overview of the TREC 2019 Fair Ranking Track. CoRR (2020)
Michael D. Ekstrand
LensKit for Python: Next-Generation Software for Recommender Systems Experiments. CIKM (2020)
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, Ben Carterette
Evaluating Stochastic Rankings with Expected Exposure. CoRR (2020)
Bamshad Mobasher, Styliani Kleanthous, Michael D. Ekstrand, Bettina Berendt, Jahna Otterbacher, Avital Shulner Tal
FairUMAP 2020: The 3rd Workshop on Fairness in User Modeling, Adaptation and Personalization. UMAP (2020)
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand
Proceedings of FACTS-IR 2019. CoRR (2019)
Michael D. Ekstrand, Joseph A. Konstan
Recommender Systems Notation: Proposed Common Notation for Teaching and Research. CoRR (2019)
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand, Adam Roegiest, Aldo Lipani, Alex Beutel, Ana Lucic, Ana-Andreea Stoica, Anubrata Das, Asia Biega, Bart Voorn, Claudia Hauff, Damiano Spina, David D. Lewis, Douglas W. Oard, Emine Yilmaz, Faegheh Hasibi, Gabriella Kazai, Graham McDonald, Hinda Haned, Iadh Ounis, Ilse van der Linden, Joris Baan, Kamuela N. Lau, Krisztian Balog, Mahmoud F. Sayed, Maria Panteli, Mark Sanderson, Matthew Lease, Preethi Lahoti, Toshihiro Kamishima
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval. SIGIR Forum 53 (2) (2019)
Michael D. Ekstrand, Robin Burke, Fernando Diaz
Fairness and Discrimination in Retrieval and Recommendation. SIGIR (2019)
Michael D. Ekstrand, Robin Burke, Fernando Diaz
Fairness and discrimination in recommendation and retrieval. RecSys (2019)
Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand
Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR). SIGIR (2019)
Bettina Berendt, Veronika Bogina, Robin Burke, Michael D. Ekstrand, Alan Hartman, Styliani Kleanthous, Tsvi Kuflik, Bamshad Mobasher, Jahna Otterbacher
FairUMAP 2019 Chairs' Welcome Overview. UMAP (Adjunct Publication) (2019)
Ashlee Milton, Michael Green, Adam Keener, Joshua Ames, Michael D. Ekstrand, Maria Soledad Pera
StoryTime: eliciting preferences from children for book recommendations. RecSys (2019)
Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver
Exploring Author Gender in Book Rating and Recommendation. CoRR (2018)
Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver
Exploring author gender in book rating and recommendation. RecSys (2018)
Toshihiro Kamishima, Pierre-Nicolas Schwab, Michael D. Ekstrand
2nd FATREC workshop: responsible recommendation. RecSys (2018)
Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel
The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction. SIGIR Forum 52 (1) (2018)
Michael D. Ekstrand, Rezvan Joshaghani, Hoda Mehrpouyan
Privacy for All: Ensuring Fair and Equitable Privacy Protections. FAT (2018)
Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442). Dagstuhl Manifestos 7 (1) (2018)
Michael D. Ekstrand, Mucun Tian, Ion Madrazo Azpiazu, Jennifer D. Ekstrand, Oghenemaro Anuyah, David McNeill, Maria Soledad Pera
All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness. FAT (2018)
Michael D. Ekstrand
The LKPY Package for Recommender Systems Experiments: Next-Generation Tools and Lessons Learned from the LensKit Project. CoRR (2018)
Bamshad Mobasher, Robin Burke, Michael D. Ekstrand, Bettina Berendt
UMAP 2018 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2018) Chairs' Welcome & Organization: Preface. UMAP (Adjunct Publication) (2018)
Michael D. Ekstrand, Amit Sharma
FATREC Workshop on Responsible Recommendation. RecSys (2017)
Michael D. Ekstrand, Vaibhav Mahant
Sturgeon and the Cool Kids: Problems with Random Decoys for Top-N Recommender Evaluation. FLAIRS Conference (2017)
Michael D. Ekstrand, Maria Soledad Pera
The Demographics of Cool: Popularity and Recommender Performance for Different Groups of Users. RecSys Posters (2017)
Sushma Channamsetty, Michael D. Ekstrand
Recommender Response to Diversity and Popularity Bias in User Profiles. FLAIRS Conference (2017)
Michael D. Ekstrand, Michael Ludwig
Dependency Injection with Static Analysis and Context-Aware Policy. J. Object Technol. 15 (1) (2016)
Michael D. Ekstrand, Martijn C. Willemsen
Behaviorism is Not Enough: Better Recommendations through Listening to Users. RecSys (2016)
Joseph A. Konstan, J. D. Walker, D. Christopher Brooks, Keith Brown, Michael D. Ekstrand
Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC. ACM Trans. Comput. Hum. Interact. 22 (2) (2015)
Michael D. Ekstrand, Daniel Kluver, F. Maxwell Harper, Joseph A. Konstan
Letting Users Choose Recommender Algorithms: An Experimental Study. RecSys (2015)
Michael D. Ekstrand, F. Maxwell Harper, Martijn C. Willemsen, Joseph A. Konstan
User perception of differences in recommender algorithms. RecSys (2014)
Joseph A. Konstan, J. D. Walker, D. Christopher Brooks, Keith Brown, Michael D. Ekstrand
Teaching recommender systems at large scale: evaluation and lessons learned from a hybrid MOOC. L@S (2014)
Tien T. Nguyen, Daniel Kluver, Ting-Yu Wang, Pik-Mai Hui, Michael D. Ekstrand, Martijn C. Willemsen, John Riedl
Rating support interfaces to improve user experience and recommender accuracy. RecSys (2013)
Daniel Kluver, Tien T. Nguyen, Michael D. Ekstrand, Shilad Sen, John Riedl
How many bits per rating? RecSys (2012)
Michael D. Ekstrand, John Riedl
When recommenders fail: predicting recommender failure for algorithm selection and combination. RecSys (2012)
Justin J. Levandoski, Mohamed Sarwat, Mohamed F. Mokbel, Michael D. Ekstrand
RecStore: an extensible and adaptive framework for online recommender queries inside the database engine. EDBT (2012)
Michael D. Ekstrand, Michael Ludwig, Jack Kolb, John Riedl
LensKit: a modular recommender framework. RecSys (2011)
Martijn C. Willemsen, Dirk G. F. M. Bollen, Michael D. Ekstrand
UCERSTI 2: second workshop on user-centric evaluation of recommender systems and their interfaces. RecSys (2011)
Michael D. Ekstrand, John Riedl, Joseph A. Konstan
Collaborative Filtering Recommender Systems. Found. Trends Hum. Comput. Interact. 4 (2) (2011)
Justin J. Levandoski, Michael D. Ekstrand, Michael Ludwig, Ahmed Eldawy, Mohamed F. Mokbel, John Riedl
RecBench: Benchmarks for Evaluating Performance of Recommender System Architectures. Proc. VLDB Endow. 4 (11) (2011)
Michael D. Ekstrand, Wei Li, Tovi Grossman, Justin Matejka, George W. Fitzmaurice
Searching for software learning resources using application context. UIST (2011)
Michael D. Ekstrand, Michael Ludwig, Joseph A. Konstan, John Riedl
Rethinking the recommender research ecosystem: reproducibility, openness, and LensKit. RecSys (2011)
Michael D. Ekstrand, Praveen Kannan, James A. Stemper, John T. Butler, Joseph A. Konstan, John Riedl
Automatically building research reading lists. RecSys (2010)
Michael D. Ekstrand, John Riedl
rv you're dumb: identifying discarded work in Wiki article history. Int. Sym. Wikis (2009)