Nir Rosenfeld

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 45

Top Topics

Automatic Classification

Discriminative Learning

Top Venues

Publications

Guy Horowitz, Yonatan Sommer, Moran Koren, Nir Rosenfeld
Classification Under Strategic Self-Selection. CoRR (2024)
Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. ICLR (2024)
Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness. CoRR (2024)
Nir Rosenfeld
Strategic ML: How to Learn With Data That 'Behaves'. WSDM (2024)
Guy Horowitz, Nir Rosenfeld
Causal Strategic Classification: A Tale of Two Shifts. CoRR (2023)
Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov
Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. CoRR (2023)
Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld
Delegated Classification. NeurIPS (2023)
Itay Eilat, Nir Rosenfeld
Performative Recommendation: Diversifying Content via Strategic Incentives. ICML (2023)
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
Strategic Classification with Graph Neural Networks. ICLR (2023)
Itay Eilat, Nir Rosenfeld
Performative Recommendation: Diversifying Content via Strategic Incentives. CoRR (2023)
Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. CoRR (2023)
Guy Horowitz, Nir Rosenfeld
Causal Strategic Classification: A Tale of Two Shifts. ICML (2023)
Elan Rosenfeld, Nir Rosenfeld
One-Shot Strategic Classification Under Unknown Costs. CoRR (2023)
Eden Saig, Nir Rosenfeld
Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement. ICML (2023)
Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld
Delegated Classification. CoRR (2023)
Eden Saig, Nir Rosenfeld
Learning to Take a Break: Sustainable Optimization of Long-Term User Engagement. CoRR (2022)
Sagi Levanon, Nir Rosenfeld
Generalized Strategic Classification and the Case of Aligned Incentives. ICML (2022)
Vineet Nair, Ganesh Ghalme, Inbal Talgam-Cohen, Nir Rosenfeld
Strategic Representation. ICML (2022)
Vineet Nair, Ganesh Ghalme, Inbal Talgam-Cohen, Nir Rosenfeld
Strategic Representation. CoRR (2022)
Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. CoRR (2022)
Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld
Strategic Classification with Graph Neural Networks. CoRR (2022)
Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. NeurIPS (2022)
Sagi Levanon, Nir Rosenfeld
Generalized Strategic Classification and the Case of Aligned Incentives. CoRR (2022)
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes
Learning Representations by Humans, for Humans. ICML (2021)
Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld
Strategic Classification in the Dark. CoRR (2021)
Sagi Levanon, Nir Rosenfeld
Strategic Classification Made Practical. ICML (2021)
Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld
Strategic Classification in the Dark. ICML (2021)
Sagi Levanon, Nir Rosenfeld
Strategic Classification Made Practical. CoRR (2021)
Nir Rosenfeld, Kojin Oshiba, Yaron Singer
Predicting Choice with Set-Dependent Aggregation. ICML (2020)
Nir Rosenfeld, Aron Szanto, David C. Parkes
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. WWW (2020)
Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes
From Predictions to Decisions: Using Lookahead Regularization. CoRR (2020)
Nir Rosenfeld, Anna Hilgard, Sai Srivatsa Ravindranath, David C. Parkes
From Predictions to Decisions: Using Lookahead Regularization. NeurIPS (2020)
Nir Rosenfeld, Aron Szanto, David C. Parkes
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. CoRR (2020)
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes
Learning Representations by Humans, for Humans. CoRR (2019)
Nir Rosenfeld, Kojin Oshiba, Yaron Singer
Predicting Choice with Set-Dependent Aggregation. CoRR (2019)
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov
Discriminative Learning of Prediction Intervals. AISTATS (2018)
Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer
Learning to Optimize Combinatorial Functions. ICML (2018)
Nir Rosenfeld, Amir Globerson
Semi-Supervised Learning with Competitive Infection Models. AISTATS (2018)
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials. WWW (Companion Volume) (2017)
Nir Rosenfeld, Amir Globerson
Semi-Supervised Learning with Competitive Infection Models. CoRR (2017)
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov
Discriminative Learning of Prediction Intervals. CoRR (2017)
Nir Rosenfeld, Amir Globerson
Optimal Tagging with Markov Chain Optimization. CoRR (2016)
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials. CoRR (2016)
Nir Rosenfeld, Mor Nitzan, Amir Globerson
Discriminative Learning of Infection Models. WSDM (2016)
Nir Rosenfeld, Amir Globerson
Optimal Tagging with Markov Chain Optimization. NIPS (2016)
Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson
Learning Structured Models with the AUC Loss and Its Generalizations. AISTATS (2014)