Jacob Abernethy

2.6k total citations
58 papers, 838 citations indexed

About

Jacob Abernethy is a scholar working on Management Science and Operations Research, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Jacob Abernethy has authored 58 papers receiving a total of 838 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Management Science and Operations Research, 33 papers in Artificial Intelligence and 13 papers in Economics and Econometrics. Recurrent topics in Jacob Abernethy's work include Advanced Bandit Algorithms Research (42 papers), Machine Learning and Algorithms (17 papers) and Auction Theory and Applications (16 papers). Jacob Abernethy is often cited by papers focused on Advanced Bandit Algorithms Research (42 papers), Machine Learning and Algorithms (17 papers) and Auction Theory and Applications (16 papers). Jacob Abernethy collaborates with scholars based in United States, Israel and Spain. Jacob Abernethy's co-authors include Alexander Rakhlin, Elad Hazan, Eric M. Schwartz, Peter L. Bartlett, Kanishka Misra, Carlos Castillo, Olivier Chapelle, Rafael Frongillo, Jennifer Wortman Vaughan and Yiling Chen and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Knowledge and Data Engineering and Marketing Science.

In The Last Decade

Jacob Abernethy

57 papers receiving 775 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jacob Abernethy United States	16	495	472	192	132	115	58	838
Onno Zoeter Netherlands	11	192 0.4×	370 0.8×	117 0.6×	38 0.3×	365 3.2×	27	915
Dávid Pál Canada	10	499 1.0×	494 1.0×	173 0.9×	26 0.2×	71 0.6×	18	790
Morteza Zadimoghaddam United States	15	199 0.4×	184 0.4×	267 1.4×	82 0.6×	43 0.4×	51	575
Katrina Ligett United States	17	368 0.7×	873 1.8×	187 1.0×	113 0.9×	68 0.6×	56	1.2k
Tyler Lu Canada	14	366 0.7×	418 0.9×	111 0.6×	330 2.5×	76 0.7×	27	856
Nisarg Shah United States	18	627 1.3×	235 0.5×	239 1.2×	687 5.2×	198 1.7×	77	1.2k
Hennie Daniels Netherlands	10	125 0.3×	269 0.6×	33 0.2×	54 0.4×	103 0.9×	46	542
Yi Cai China	17	136 0.3×	419 0.9×	57 0.3×	35 0.3×	203 1.8×	58	792
Tomasz Michalak Poland	18	438 0.9×	213 0.5×	126 0.7×	473 3.6×	47 0.4×	99	987
Gagan Aggarwal United States	15	437 0.9×	537 1.1×	303 1.6×	66 0.5×	151 1.3×	32	1.2k

Countries citing papers authored by Jacob Abernethy

Since Specialization

Citations

This map shows the geographic impact of Jacob Abernethy'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 Jacob Abernethy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacob Abernethy more than expected).

Fields of papers citing papers by Jacob Abernethy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob Abernethy. 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 Jacob Abernethy. The network helps show where Jacob Abernethy may publish in the future.

Co-authorship network of co-authors of Jacob Abernethy

This figure shows the co-authorship network connecting the top 25 collaborators of Jacob Abernethy. A scholar is included among the top collaborators of Jacob Abernethy 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 Jacob Abernethy. Jacob Abernethy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Abernethy, Jacob, et al.. (2021). Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization.. 3–47. 1 indexed citations

Abernethy, Jacob, et al.. (2021). Observation-Free Attacks on Stochastic Bandits. Neural Information Processing Systems. 34. 1 indexed citations

Abernethy, Jacob, et al.. (2019). Learning Auctions with Robust Incentive Guarantees. Neural Information Processing Systems. 32. 11587–11597. 4 indexed citations

Abernethy, Jacob, et al.. (2019). Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games. International Conference on Machine Learning. 921–930. 7 indexed citations

Abernethy, Jacob, et al.. (2019). Online Learning via the Differential Privacy Lens. Neural Information Processing Systems. 32. 8894–8904.

Abernethy, Jacob, et al.. (2018). Faster Rates for Convex-Concave Games. Conference on Learning Theory. 1595–1625. 1 indexed citations

Abernethy, Jacob, et al.. (2017). On Frank-Wolfe and Equilibrium Computation. Neural Information Processing Systems. 30. 6584–6593. 8 indexed citations

Abernethy, Jacob, et al.. (2017). How to Train Your DRAGAN. arXiv (Cornell University). 12 indexed citations

Abernethy, Jacob, et al.. (2017). Online Learning via Differential Privacy.. arXiv (Cornell University). 2 indexed citations

10.

Abernethy, Jacob, Kareem Amin, & Ruihao Zhu. (2016). Threshold Bandits, With and Without Censored Feedback. Neural Information Processing Systems. 29. 4889–4897. 6 indexed citations

11.

Abernethy, Jacob & Elad Hazan. (2016). Faster convex optimization: simulated annealing with an efficient universal barrier. International Conference on Machine Learning. 2520–2528. 1 indexed citations

12.

Waggoner, Bo, Rafael Frongillo, & Jacob Abernethy. (2015). A market framework for eliciting private data. Neural Information Processing Systems. 28. 3510–3518. 4 indexed citations

13.

Abernethy, Jacob, Kareem Amin, Michael Kearns, & Moez Draief. (2013). Large-Scale Bandit Problems and KWIK Learning. International Conference on Machine Learning. 588–596. 5 indexed citations

14.

Abernethy, Jacob & Satyen Kale. (2013). Adaptive Market Making via Online Learning. Neural Information Processing Systems. 26. 2058–2066. 10 indexed citations

15.

Abernethy, Jacob & Shie Mannor. (2011). Does an Efficient Calibrated Forecasting Strategy Exist. Conference on Learning Theory. 809–812. 2 indexed citations

16.

Abernethy, Jacob. (2010). Can we learn to gamble efficiently. Conference on Learning Theory. 318–319. 5 indexed citations

17.

Abernethy, Jacob & Alexander Rakhlin. (2009). An Efficient Bandit Algorithm for sqrt(T) Regret in Online Multiclass Prediction. Conference on Learning Theory. 4 indexed citations

18.

Abernethy, Jacob & Alexander Rakhlin. (2009). Beating the adaptive bandit with high probability. ScholarlyCommons (University of Pennsylvania). 15 indexed citations

19.

Abernethy, Jacob & Manfred K. Warmuth. (2009). Minimax games with bandits. Conference on Learning Theory. 1 indexed citations

20.

Abernethy, Jacob, Elad Hazan, & Alexander Rakhlin. (2008). Competing in the dark: An efficient algorithm for bandit linear optimization. ScholarlyCommons (University of Pennsylvania). 263–274. 99 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.

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