Mikhail Bilenko

4.9k citations
29 papers · 3.0k indexed · 3 hit papers · h-index 17

Mikhail Bilenko

29 papers receiving 2.8k citations

Hit Papers

Integrating constraints and metric learning in semi-super...5252003202620102018100200300400500

Peers

Mikhail Bilenko
Comparison fields: 5 of 116
  • Management Science and Operations Research 1.0k
  • Artificial Intelligence 1.9k
  • Signal Processing 493
  • Information Systems 1.0k
  • Computer Vision and Pattern Recognition 649
Replace Shuai Ma with:
Shuai Ma China
Chris Cornelis Belgium
Jun Ma China
Dayne Freitag United States
Αλέξανδρος Νανόπουλος Germany
Kurt Bollacker United States
Venkatesh Ganti United States
Defu Lian China
Steven Minton United States
Domonkos Tikk Hungary
Mikhail Bilenko relative to Shuai Ma China Shuai Ma's profile →
Citations per field
00.5×1.6×
Shuai Ma · 1×
Citations per year

Countries citing papers authored by Mikhail Bilenko

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Bilenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Mikhail Bilenko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mikhail Bilenko Line = papers co-authored together Mikhail Bilenko links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201637
2
Lazy paired hyper-parameter tuning
20137
3 20123
4
Axiomatic Analysis of Co-occurrence Similarity Functions
20122
5
Targeted, Not Tracked: Client-Side Solutions for Privacy-Friendly Behavioral Advertising
201111
6 2011136
7
Scaling up Machine Learning
201114
8 200912
9 20092
10 2008114
11 200820
12 200813
13
Intelligent information acquisition for improved clustering
20071
14 2007134
15 2006151
16
Learnable similarity functions and their applications to clustering and record linkage
20047
17
A probabilistic framework for semi-supervised clusteringbreakdown →
2004512
18
Integrating constraints and metric learning in semi-supervised clusteringbreakdown →
2004525
19
Employing Trainable String Similarity Metrics for Information Integration
200310
20
Comparing and Unifying Search-Based and Similarity-Based Approaches to Semi-Supervised Clustering
200354

About Mikhail Bilenko

Mikhail Bilenko is a scholar working on Management Science and Operations Research, Artificial Intelligence, Information Systems, Signal Processing and Statistical and Nonlinear Physics, having authored 29 papers that have together received 3.0k indexed citations. Recurring topics across this work include Data Quality and Management (9 papers), Web Data Mining and Analysis (7 papers), Topic Modeling (5 papers), Information Retrieval and Search Behavior (5 papers), Privacy-Preserving Technologies in Data (4 papers), Recommender Systems and Techniques (4 papers), Advanced Clustering Algorithms Research (4 papers) and Machine Learning and Algorithms (3 papers). The work is most often cited by research in Management Science and Operations Research (1.0k citations), Artificial Intelligence (1.9k citations), Signal Processing (493 citations), Information Systems (1.0k citations) and Computer Vision and Pattern Recognition (649 citations). Mikhail Bilenko has collaborated with scholars based in United States, Finland and United Kingdom. Frequent co-authors include Raymond J. Mooney, Sugato Basu, Ryen W. White, John Langford, Ron Bekkerman, William W. Cohen, Pradeep Ravikumar, Stephen E. Fienberg, Silviu Cucerzan and Matthew Richardson. Their work appears in journals such as ACM Transactions on the Web, IEEE Intelligent Systems, ACM SIGIR Forum, arXiv (Cornell University) and International Joint Conference on Artificial Intelligence.

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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