Mitchell Stern
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Adversarial Robustness in Machine Learning
- Stochastic Gradient Optimization Techniques
- Speech and dialogue systems
- Software top 10%
Papers in ⓘ
-
- Natural Language Processing Techniques 6
- Topic Modeling 6
- Speech Recognition and Synthesis 2
- Speech and dialogue systems 2
- Stochastic Gradient Optimization Techniques 2
- Software 1
- Software Testing and Debugging Techniques 1
- Co-authors
- Dan Klein (4 shared papers)Maxim Rabinovich (1 shared paper)Jacob Andreas (1 shared paper)Jamie Kiros (2 shared papers)William Chan (2 shared papers)Jakob Uszkoreit (2 shared papers)Eric Wallace (1 shared paper)Dawn Song (1 shared paper)
- Journals
- Chemical Communications (1 paper)arXiv (Cornell University) (1 paper)Neural Information Processing Systems (3 papers)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Mitchell Stern
11 papers receiving 473 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 438
- Software 37
- Computer Vision and Pattern Recognition 133
- Information Systems 106
- Signal Processing 42
Countries citing papers authored by Mitchell Stern
This map shows the geographic impact of Mitchell Stern'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 Mitchell Stern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mitchell Stern more than expected).
Fields of papers citing papers by Mitchell Stern
This network shows the impact of papers produced by Mitchell Stern. 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 Mitchell Stern. The network helps show where Mitchell Stern may publish in the future.
Co-authors
The 25 scholars most cited alongside Mitchell Stern, 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 | 2017 | 159 | |
| 2 | 2017 | 93 | |
| 3 | The Marginal Value of Adaptive Gradient Methods in Machine Learning | 2017 | 65 |
| 4 | 2019 | 60 | |
| 5 | 2020 | 43 | |
| 6 | 2018 | 36 | |
| 7 | 2017 | 29 | |
| 8 | Stochastic Cubic Regularization for Fast Nonconvex Optimization | 2018 | 20 |
| 9 | Kernel feature selection via conditional covariance minimization | 2017 | 7 |
| 10 | 2023 | 6 | |
| 11 | 2020 | 2 |
About Mitchell Stern
Mitchell Stern is a scholar working on Artificial Intelligence, Software, Management Science and Operations Research, Statistics and Probability and Signal Processing, having authored 11 papers that have together received 520 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers), Advanced Bandit Algorithms Research (2 papers), Speech Recognition and Synthesis (2 papers), Speech and dialogue systems (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Advanced Malware Detection Techniques (1 paper) and Software Testing and Debugging Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (438 citations), Software (37 citations), Computer Vision and Pattern Recognition (133 citations), Information Systems (106 citations) and Signal Processing (42 citations). Mitchell Stern has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Dan Klein, Maxim Rabinovich, Jacob Andreas, Jamie Kiros, William Chan, Jakob Uszkoreit, Eric Wallace, Dawn Song, Ashia Wilson and Rebecca Roelofs. Their work appears in journals such as Chemical Communications, arXiv (Cornell University) and Neural Information Processing Systems.
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.