Randomized Online Algorithms
Randomized Online Algorithms is an algorithmic paradigm that belongs to the class of online algorithms, distinguished by its use of randomness in decision-making to handle input sequences revealed incrementally over time without knowledge of future events.
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13.2K
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526
Authors
226
Institutions
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2017–2026
58
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Logarithmic regret algorithms for online convex optimization
Elad Hazan, Amit Agarwal, Satyen Kale · Machine Learning · 2007 · 874 citations · Full text
Ondřej Chum, Jiřı́ Matas · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2008 · 439 citations
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Tel Aviv University
Tel Aviv, Israel
15 h-index
33 publications
940 citations
Technion – Israel Institute of Technology
Haifa, Israel
14 h-index
21 publications
1.6K citations

University of Toronto
Toronto, Canada
11 h-index
14 publications
1.1K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
24 publications
1.1K citations
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
12 publications
1.5K citations
Microsoft (United States)
Redmond, United States
9 h-index
12 publications
649 citations
Stanford University
Stanford, United States
8 h-index
13 publications
604 citations
University of California, Riverside
Riverside, United States
8 h-index
10 publications
512 citations
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Repository · 18 publications · 424 citations
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11 publications · 460 citations
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10 publications · 857 citations
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8 publications · 344 citations
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Repository · 7 publications · 131 citations
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