Vladimir Eidelman
- Artificial Intelligence top 5%
- Topic Modeling 11
- Natural Language Processing Techniques 11
- Text and Document Classification Technologies 3
- Speech and dialogue systems 2
- Neural Networks and Applications 1
- Machine Learning and Algorithms 1
- General Social Sciences top 10%
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- Handwritten Text Recognition Techniques 1
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- Judicial and Constitutional Studies 1
- Co-authors
- Philip ResnikJordan Boyd‐GraberFerhan TüreJuri GanitkevitchJonathan WeeseHendra SetiawanChris DyerAdam Lopez
- Journals
- The Notre Dame law review (1 paper)Language Resources and Evaluation (1 paper)Workshop on Statistical Machine Translation (2 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Vladimir Eidelman
15 papers receiving 409 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 444
- General Social Sciences 9
- Computer Vision and Pattern Recognition 45
- Information Systems 32
- Computer Science Applications 7
Countries citing papers authored by Vladimir Eidelman
This map shows the geographic impact of Vladimir Eidelman'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 Vladimir Eidelman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladimir Eidelman more than expected).
Fields of papers citing papers by Vladimir Eidelman
This network shows the impact of papers produced by Vladimir Eidelman. 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 Vladimir Eidelman. The network helps show where Vladimir Eidelman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vladimir Eidelman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 1 | |
| 2 | Computationally Assisted Regulatory Participation | 2018 | 8 |
| 3 | 2014 | 33 | |
| 4 | Online Relative Margin Maximization for Statistical Machine Translation | 2013 | 4 |
| 5 | Mr. MIRA: Open-Source Large-Margin Structured Learning on MapReduce | 2013 | 2 |
| 6 | Topic Models for Dynamic Translation Model Adaptation | 2012 | 55 |
| 7 | Optimization Strategies for Online Large-Margin Learning in Machine Translation | 2012 | 13 |
| 8 | Noisy SMS Machine Translation in Low-Density Languages | 2011 | 3 |
| 9 | The Value of Monolingual Crowdsourcing in a Real-World Translation Scenario: Simulation using Haitian Creole Emergency SMS Messages | 2011 | 13 |
| 10 | cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models | 2010 | 176 |
| 11 | Lessons Learned in Part-of-Speech Tagging of Conversational Speech | 2010 | 8 |
| 12 | 2009 | 27 | |
| 13 | BART: A modular toolkit for coreference resolution | 2008 | 88 |
| 14 | 2008 | 30 | |
| 15 | 2008 | 4 |
About Vladimir Eidelman
Vladimir Eidelman is a scholar working on Artificial Intelligence, Computer Science Applications, Law, Computer Vision and Pattern Recognition and Strategy and Management, having authored 15 papers that have together received 465 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers), Text and Document Classification Technologies (3 papers), Speech and dialogue systems (2 papers), Neural Networks and Applications (1 paper), Handwritten Text Recognition Techniques (1 paper), Machine Learning and Algorithms (1 paper) and Judicial and Constitutional Studies (1 paper). The work is most often cited by research in Artificial Intelligence (444 citations), General Social Sciences (9 citations), Computer Vision and Pattern Recognition (45 citations), Information Systems (32 citations) and Computer Science Applications (7 citations). Vladimir Eidelman has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Philip Resnik, Jordan Boyd‐Graber, Ferhan Türe, Juri Ganitkevitch, Jonathan Weese, Hendra Setiawan, Chris Dyer, Adam Lopez, Phil Blunsom and Jason Smith. Their work appears in journals such as The Notre Dame law review, Language Resources and Evaluation, Workshop on Statistical Machine Translation, Edinburgh Research Explorer (University of Edinburgh) and Meeting of the Association for Computational Linguistics.
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.