Kevin Jamieson

4.2k total citations · 1 hit paper
34 papers, 984 citations indexed

About

Kevin Jamieson is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kevin Jamieson has authored 34 papers receiving a total of 984 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 17 papers in Management Science and Operations Research and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kevin Jamieson's work include Advanced Bandit Algorithms Research (17 papers), Machine Learning and Algorithms (11 papers) and Machine Learning and Data Classification (9 papers). Kevin Jamieson is often cited by papers focused on Advanced Bandit Algorithms Research (17 papers), Machine Learning and Algorithms (11 papers) and Machine Learning and Data Classification (9 papers). Kevin Jamieson collaborates with scholars based in United States, Switzerland and China. Kevin Jamieson's co-authors include Ameet Talwalkar, Afshin Rostamizadeh, Giulia DeSalvo, Lisha Li, Robert D. Nowak, Benjamin Recht, Ekaterina Gonina, Moritz Hardt, Liam Li and Lalit Jain and has published in prestigious journals such as IEEE Transactions on Signal Processing, PLoS Computational Biology and Journal of Machine Learning Research.

In The Last Decade

Kevin Jamieson

32 papers receiving 927 citations

Hit Papers

Hyperband: a novel bandit-based approach to hyperparamete... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers

Kevin Jamieson
Aaron Klein Germany
Qiang Fu China
Jonathan Baxter Australia
Kenneth W. Bauer United States
Kai Wu China
Qingquan Song United States
En Fan China
Aaron Klein Germany
Kevin Jamieson
Citations per year, relative to Kevin Jamieson Kevin Jamieson (= 1×) peers Aaron Klein

Countries citing papers authored by Kevin Jamieson

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Jamieson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Jamieson

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Jamieson. A scholar is included among the top collaborators of Kevin Jamieson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kevin Jamieson. Kevin Jamieson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Yifang, Stephen Mussmann, Jeff Bilmes, et al.. (2024). An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. 6549–6560. 2 indexed citations
2.
Jamieson, Kevin, et al.. (2023). Demonstrating Large-Scale Package Manipulation via Learned Metrics of Pick Success. 2 indexed citations
3.
Jain, Lalit, et al.. (2022). Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design. PLoS Computational Biology. 18(7). e1010311–e1010311. 1 indexed citations
4.
Simchowitz, Max, et al.. (2021). Task-Optimal Exploration in Linear Dynamical Systems. International Conference on Machine Learning. 10641–10652. 1 indexed citations
5.
Li, Liam, Kevin Jamieson, Afshin Rostamizadeh, et al.. (2020). A System for Massively Parallel Hyperparameter Tuning. 2. 230–246. 87 indexed citations
6.
Jamieson, Kevin, et al.. (2019). The True Sample Complexity of Identifying Good Arms.. International Conference on Artificial Intelligence and Statistics. 1781–1791. 1 indexed citations
7.
Jamieson, Kevin & Lalit Jain. (2018). A Bandit Approach to Sequential Experimental Design with False Discovery Control. Neural Information Processing Systems. 31. 3660–3670. 4 indexed citations
8.
Jain, Lalit & Kevin Jamieson. (2018). Firing Bandits: Optimizing Crowdfunding. International Conference on Machine Learning. 2206–2214. 1 indexed citations
9.
Li, Lisha, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, & Ameet Talwalkar. (2017). Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. International Conference on Learning Representations. 40 indexed citations
10.
Yang, Fanny, Aaditya Ramdas, Kevin Jamieson, & Martin J. Wainwright. (2017). A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control. Neural Information Processing Systems. 30. 5957–5966. 3 indexed citations
11.
Li, Lisha, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, & Ameet Talwalkar. (2017). Hyperband: a novel bandit-based approach to hyperparameter optimization. Journal of Machine Learning Research. 18(1). 6765–6816. 510 indexed citations breakdown →
12.
Jamieson, Kevin & Ameet Talwalkar. (2016). Non-stochastic Best Arm Identification and Hyperparameter Optimization. International Conference on Artificial Intelligence and Statistics. 240–248. 44 indexed citations
13.
Jun, Kwang-Sung, Kevin Jamieson, Robert D. Nowak, & Xiaojin Zhu. (2016). Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls. International Conference on Artificial Intelligence and Statistics. 139–148. 6 indexed citations
14.
Jamieson, Kevin, Daniel Haas, & Benjamin Recht. (2016). The Power of Adaptivity in Identifying Statistical Alternatives. Neural Information Processing Systems. 29. 775–783. 3 indexed citations
15.
Jain, Lalit, Kevin Jamieson, & Robert D. Nowak. (2016). Finite Sample Prediction and Recovery Bounds for Ordinal Embedding. Neural Information Processing Systems. 29. 2703–2711. 12 indexed citations
16.
Jamieson, Kevin, Sumeet Katariya, Atul Deshpande, & Robert D. Nowak. (2015). Sparse Dueling Bandits. International Conference on Artificial Intelligence and Statistics. 416–424. 7 indexed citations
17.
Jamieson, Kevin, et al.. (2015). NEXT: a system for real-world development, evaluation, and application of active learning. Neural Information Processing Systems. 28. 2656–2664. 23 indexed citations
18.
Jamieson, Kevin, Matthew Malloy, Robert D. Nowak, & Sébastien Bubeck. (2014). lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits. Conference on Learning Theory. 423–439. 40 indexed citations
19.
Jamieson, Kevin, Robert D. Nowak, & Ben Recht. (2012). Query Complexity of Derivative-Free Optimization. Neural Information Processing Systems. 25. 2672–2680. 18 indexed citations
20.
Jamieson, Kevin, et al.. (2009). Sequential Bayesian estimation of the probability of detection for tracking. International Conference on Information Fusion. 641–648. 13 indexed citations

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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