Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Fairness through awareness
20121.6k citationsCynthia Dwork, Moritz Hardt et al.profile →
Understanding deep learning (still) requires rethinking generalization
20211.3k citationsChiyuan Zhang, Samy Bengio et al.Communications of the ACMprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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This map shows the geographic impact of Moritz Hardt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Moritz Hardt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moritz Hardt more than expected).
This network shows the impact of papers produced by Moritz Hardt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Moritz Hardt. The network helps show where Moritz Hardt may publish in the future.
Co-authorship network of co-authors of Moritz Hardt
This figure shows the co-authorship network connecting the top 25 collaborators of Moritz Hardt.
A scholar is included among the top collaborators of Moritz Hardt based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Moritz Hardt. Moritz Hardt is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Li, Liam, Kevin Jamieson, Afshin Rostamizadeh, et al.. (2020). A System for Massively Parallel Hyperparameter Tuning. 2. 230–246.87 indexed citations
4.
Zhang, Chiyuan, Samy Bengio, Moritz Hardt, Michael C. Mozer, & Yoram Singer. (2020). Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. arXiv (Cornell University).6 indexed citations
5.
Hardt, Moritz, et al.. (2019). Natural Analysts in Adaptive Data Analysis.. International Conference on Machine Learning. 7703–7711.1 indexed citations
6.
Roelofs, Rebecca, Vaishaal Shankar, Benjamin Recht, et al.. (2019). A Meta-Analysis of Overfitting in Machine Learning. Neural Information Processing Systems. 32. 9175–9185.53 indexed citations
7.
Miller, J. J. & Moritz Hardt. (2018). When Recurrent Models Don't Need To Be Recurrent.. arXiv (Cornell University).6 indexed citations
8.
Miller, J. J. & Moritz Hardt. (2018). Stable Recurrent Models.. International Conference on Learning Representations.9 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.