D. Sculley
Impact in
- Artificial Intelligence top 0.5%
- Machine Learning and Data Classification
- Data Stream Mining Techniques
- Text and Document Classification Technologies
- Anomaly Detection Techniques and Applications
- Topic Modeling
- Health Informatics top 2%
Papers in
-
- Machine Learning and Algorithms 7
- Text and Document Classification Technologies 6
- Machine Learning and Data Classification 5
- Explainable Artificial Intelligence (XAI) 4
- Data Stream Mining Techniques 3
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- Spam and Phishing Detection 11
- Software Engineering Research 3
- Co-authors
- Daniel Golovin (5 shared papers)Gabriel Wachman (3 shared papers)Gary D. Holt (3 shared papers)Todd Phillips (3 shared papers)Michael Young (3 shared papers)Eugene Davydov (3 shared papers)Dietmar Ebner (3 shared papers)John Karro (2 shared papers)
- Journals
- Nature Biotechnology (1 paper)ACS Central Science (1 paper)Lecture notes in computer science (2 papers)Literary and Linguistic Computing (2 papers)International Conference on Learning Representations (1 paper)
- Partner nations
- United StatesSpainIran
In The Last Decade
D. Sculley
40 papers receiving 3.6k citations
D. Sculley's Hit Papers
Peers
Comparison fields: 5 of 179
- Artificial Intelligence 2.0k
- Health Informatics 69
- Information Systems 1.1k
- Computer Vision and Pattern Recognition 718
- Management Science and Operations Research 370
Countries citing papers authored by D. Sculley
This map shows the geographic impact of D. Sculley'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 D. Sculley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Sculley more than expected).
Fields of papers citing papers by D. Sculley
This network shows the impact of papers produced by D. Sculley. 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 D. Sculley. The network helps show where D. Sculley may publish in the future.
Co-authors
The 25 scholars most cited alongside D. Sculley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Web-scale k-means clustering Hit paper breakdown → | 2010 | 762 |
| 2 | Ad click prediction Hit paper breakdown → | 2013 | 556 |
| 3 | Hidden technical debt in Machine learning systems Hit paper breakdown → | 2015 | 544 |
| 4 | Google Vizier Hit paper breakdown → | 2017 | 314 |
| 5 | 2007 | 189 | |
| 6 | Using deep learning to annotate the protein universe Hit paper breakdown → | 2022 | 174 |
| 7 | Machine Learning: The High Interest Credit Card of Technical Debt | 2014 | 141 |
| 8 | 2017 | 138 | |
| 9 | 2019 | 136 | |
| 10 | Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift | 2019 | 104 |
| 11 | 2010 | 98 | |
| 12 | 2020 | 97 | |
| 13 | 2009 | 89 | |
| 14 | 2007 | 73 | |
| 15 | 2006 | 71 | |
| 16 | Online Active Learning Methods for Fast Label-Efficient Spam Filtering. | 2007 | 67 |
| 17 | Winner's Curse? On Pace, Progress, and Empirical Rigor. | 2018 | 61 |
| 18 | 2011 | 56 | |
| 19 | 2008 | 54 | |
| 20 | Spam Filtering Using Inexact String Matching in Explicit Feature Space with On-Line Linear Classifiers. | 2006 | 30 |
About D. Sculley
D. Sculley is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Management Science and Operations Research, having authored 40 papers that have together received 4.0k indexed citations. Recurring topics across this work include Spam and Phishing Detection (11 papers), Machine Learning and Algorithms (7 papers), Text and Document Classification Technologies (6 papers), Machine Learning and Data Classification (5 papers), Explainable Artificial Intelligence (XAI) (4 papers), Scientific Computing and Data Management (3 papers), Software Engineering Research (3 papers) and Data Stream Mining Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (2.0k citations), Health Informatics (69 citations), Information Systems (1.1k citations), Computer Vision and Pattern Recognition (718 citations) and Management Science and Operations Research (370 citations). D. Sculley has collaborated with scholars based in United States, Spain and Iran. Frequent co-authors include Daniel Golovin, Gabriel Wachman, Gary D. Holt, Todd Phillips, Michael Young, Eugene Davydov, Dietmar Ebner, John Karro, Greg Kochanski and Subhodeep Moitra. Their work appears in journals such as Nature Biotechnology, ACS Central Science, Lecture notes in computer science, Literary and Linguistic Computing and International Conference on Learning Representations.
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.