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ORCIDNir Rosenfeld
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2020 – today
- 2024
[c25]Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld:
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. ICLR 2024- [c24]Guy Horowitz, Yonatan Sommer, Moran Koren, Nir Rosenfeld:
Classification Under Strategic Self-Selection. ICML 2024 - [c23]Elan Rosenfeld, Nir Rosenfeld:
One-Shot Strategic Classification Under Unknown Costs. ICML 2024 - [c22]Nir Rosenfeld
:
Strategic ML: How to Learn With Data That 'Behaves'. WSDM 2024: 1128-1131 - [i23]Guy Horowitz, Yonatan Sommer, Moran Koren, Nir Rosenfeld:
Classification Under Strategic Self-Selection. CoRR abs/2402.15274 (2024) - [i22]Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld:
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness. CoRR abs/2406.11458 (2024) - 2023
- [c21]Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld:
Strategic Classification with Graph Neural Networks. ICLR 2023 - [c20]Itay Eilat, Nir Rosenfeld:
Performative Recommendation: Diversifying Content via Strategic Incentives. ICML 2023: 9082-9103 - [c19]Guy Horowitz, Nir Rosenfeld:
Causal Strategic Classification: A Tale of Two Shifts. ICML 2023: 13233-13253 - [c18]Eden Saig, Nir Rosenfeld:
Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement. ICML 2023: 29671-29696 - [c17]Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld:
Delegated Classification. NeurIPS 2023 - [i21]Itay Eilat, Nir Rosenfeld:
Performative Recommendation: Diversifying Content via Strategic Incentives. CoRR abs/2302.04336 (2023) - [i20]Guy Horowitz, Nir Rosenfeld:
Causal Strategic Classification: A Tale of Two Shifts. CoRR abs/2302.06280 (2023) - [i19]Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld:
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. CoRR abs/2306.10606 (2023) - [i18]Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld:
Delegated Classification. CoRR abs/2306.11475 (2023) - [i17]Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov:
Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. CoRR abs/2308.00225 (2023) - [i16]Elan Rosenfeld, Nir Rosenfeld:
One-Shot Strategic Classification Under Unknown Costs. CoRR abs/2311.02761 (2023) - 2022
- [c16]Sagi Levanon, Nir Rosenfeld:
Generalized Strategic Classification and the Case of Aligned Incentives. ICML 2022: 12593-12618 - [c15]Vineet Nair, Ganesh Ghalme, Inbal Talgam-Cohen, Nir Rosenfeld:
Strategic Representation. ICML 2022: 16331-16352 - [c14]Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld:
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. NeurIPS 2022 - [i15]Sagi Levanon, Nir Rosenfeld:
Generalized Strategic Classification and the Case of Aligned Incentives. CoRR abs/2202.04357 (2022) - [i14]Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld:
Strategic Classification with Graph Neural Networks. CoRR abs/2205.15765 (2022) - [i13]Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld:
In the Eye of the Beholder: Robust Prediction with Causal User Modeling. CoRR abs/2206.00416 (2022) - [i12]Vineet Nair, Ganesh Ghalme, Inbal Talgam-Cohen, Nir Rosenfeld:
Strategic Representation. CoRR abs/2206.08542 (2022) - [i11]Eden Saig, Nir Rosenfeld:
Learning to Take a Break: Sustainable Optimization of Long-Term User Engagement. CoRR abs/2211.13585 (2022) - 2021
- [c13]Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld:
Strategic Classification in the Dark. ICML 2021: 3672-3681 - [c12]Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes:
Learning Representations by Humans, for Humans. ICML 2021: 4227-4238 - [c11]Sagi Levanon, Nir Rosenfeld:
Strategic Classification Made Practical. ICML 2021: 6243-6253 - [i10]Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld:
Strategic Classification in the Dark. CoRR abs/2102.11592 (2021) - [i9]Sagi Levanon, Nir Rosenfeld:
Strategic Classification Made Practical. CoRR abs/2103.01826 (2021) - 2020
- [c10]Nir Rosenfeld, Kojin Oshiba, Yaron Singer:
Predicting Choice with Set-Dependent Aggregation. ICML 2020: 8220-8229 - [c9]Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes:
From Predictions to Decisions: Using Lookahead Regularization. NeurIPS 2020 - [c8]Nir Rosenfeld, Aron Szanto, David C. Parkes:
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. WWW 2020: 1018-1028 - [i8]Nir Rosenfeld, Aron Szanto, David C. Parkes:
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. CoRR abs/2002.00850 (2020) - [i7]Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes:
From Predictions to Decisions: Using Lookahead Regularization. CoRR abs/2006.11638 (2020)
2010 – 2019
- 2019
- [i6]Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes:
Learning Representations by Humans, for Humans. CoRR abs/1905.12686 (2019) - [i5]Nir Rosenfeld, Kojin Oshiba, Yaron Singer:
Predicting Choice with Set-Dependent Aggregation. CoRR abs/1906.06365 (2019) - 2018
- [b1]Nir Rosenfeld:
Machine Learning : Of, By, and For Social Dynamics (כותר נוסף בעברית: מערכות למודות : של, על, ועבור דינמיקה חברתית). Hebrew University of Jerusalem, Israel, 2018 - [c7]Nir Rosenfeld, Amir Globerson:
Semi-Supervised Learning with Competitive Infection Models. AISTATS 2018: 336-346 - [c6]Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov:
Discriminative Learning of Prediction Intervals. AISTATS 2018: 347-355 - [c5]Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer:
Learning to Optimize Combinatorial Functions. ICML 2018: 4371-4380 - 2017
- [c4]Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov:
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials. WWW (Companion Volume) 2017: 602-609 - [i4]Nir Rosenfeld, Amir Globerson:
Semi-Supervised Learning with Competitive Infection Models. CoRR abs/1703.06426 (2017) - [i3]Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov:
Discriminative Learning of Prediction Intervals. CoRR abs/1710.05888 (2017) - 2016
- [c3]Nir Rosenfeld, Amir Globerson:
Optimal Tagging with Markov Chain Optimization. NIPS 2016: 1307-1315 - [c2]Nir Rosenfeld, Mor Nitzan, Amir Globerson:
Discriminative Learning of Infection Models. WSDM 2016: 563-572 - [i2]Nir Rosenfeld, Amir Globerson:
Optimal Tagging with Markov Chain Optimization. CoRR abs/1605.04719 (2016) - [i1]Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov:
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials. CoRR abs/1610.07667 (2016) - 2014
- [c1]Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson:
Learning Structured Models with the AUC Loss and Its Generalizations. AISTATS 2014: 841-849
Coauthor Index
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