Martin Zinkevich

42 papers receiving 3.0k citations

Hit Papers

Online convex programming and generalized infinitesimal g...200320262010201820032010250500750

Peers

Martin Zinkevich
Comparison fields: 5 of 119
  • Artificial Intelligence 2.3k
  • Management Science and Operations Research 1.1k
  • Computer Networks and Communications 619
  • Computer Vision and Pattern Recognition 515
  • Economics and Econometrics 287
Replace Csaba Szepesvári with:
Csaba Szepesvári Canada
Lihong Li United States
Ran El‐Yaniv Israel
Weike Pan China
Michael Bowling Canada
Christopher Ré United States
Chris Cornelis Belgium
Fei Sun China
David Cohn United States
Xiang Ren United States
Martin Zinkevich relative to Csaba Szepesvári Canada Csaba Szepesvári's profile →
Citations per field
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Csaba Szepesvári · 1×
Citations per year

Countries citing papers authored by Martin Zinkevich

Since Specialization
Citations

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

Fields of papers citing papers by Martin Zinkevich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Zinkevich

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Holographic Feature Representations of Deep Networks.
0
2
Deep learning games
6
3 42
4
Parallelized Stochastic Gradient Descentbreakdown →
623
5 10
6
A Practical Use of Imperfect Recall
37
7
Slow Learners are Fast
97
8 4
9
A Fast Way to Produce Optimal Fixed-Depth Decision Trees.
6
10
A new algorithm for generating equilibria in massive zero-sum games
27
11
Approximate) Subgradient Methods for Structured Prediction
22
12 2
13
Prob-Max n : playing N-player games with opponent models
21
14
Optimal unbiased estimators for evaluating agent performance
14
15
Boosting expert ensembles for rapid concept recall
7
16
Cyclic Equilibria in Markov Games
29
17
Online convex programming and generalized infinitesimal gradient ascentbreakdown →
930
18
Competitive Analysis of the Explore/Exploit Tradeoff
0
19 17
20
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning
17

About Martin Zinkevich

Martin Zinkevich is a scholar working on Management Science and Operations Research, Artificial Intelligence and General Decision Sciences, having authored 45 papers that have together received 3.3k indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (13 papers), Machine Learning and Algorithms (11 papers) and Artificial Intelligence in Games (9 papers). The work is most often cited by research in Management Science and Operations Research (1.1k citations), Artificial Intelligence (2.3k citations) and Computer Networks and Communications (619 citations). Martin Zinkevich has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Alex Smola, Lihong Li, Markus Weimer, Michael Bowling, Nathan Ratliff, J. Andrew Bagnell, Michael Johanson, Neoklis Polyzotis, Sudip Roy and Steven Euijong Whang. Their work appears in journals such as Artificial Intelligence, Journal of the ACM and ACM SIGMOD Record.

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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