John C. Duchi
- Artificial Intelligence top 0.1%
- Stochastic Gradient Optimization Techniques 37
- Machine Learning and Algorithms 14
- Privacy-Preserving Technologies in Data 13
- Computational Mathematics top 2%
- Computational Mechanics top 0.5%
- Sparse and Compressive Sensing Techniques 25
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- Advanced Bandit Algorithms Research 15
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- Statistical Methods and Inference 13
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- Advanced Optimization Algorithms Research 8
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- Complexity and Algorithms in Graphs 6
- Co-authors
- Yoram SingerElad HazanMartin J. WainwrightMichael I. JordanShai Shalev‐ShwartzTushar ChandraAlekh AgarwalYuchen Zhang
- Journals
- SIAM Journal on Optimization (5 papers)The Annals of Statistics (4 papers)Journal of Machine Learning Research (3 papers)
- Partner nations
- United StatesIsraelSweden
In The Last Decade
John C. Duchi
77 papers receiving 8.3k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Artificial Intelligence 5.5k
- Computer Vision and Pattern Recognition 2.0k
- Computational Mathematics 57
- Computational Mechanics 1.5k
- Management Science and Operations Research 825
Countries citing papers authored by John C. Duchi
This map shows the geographic impact of John C. Duchi'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 John C. Duchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John C. Duchi more than expected).
Fields of papers citing papers by John C. Duchi
This network shows the impact of papers produced by John C. Duchi. 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 John C. Duchi. The network helps show where John C. Duchi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John C. Duchi, 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 | Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms | 2020 | 8 |
| 2 | Knowing what you know: valid confidence sets in multiclass and multilabel prediction. | 2020 | 1 |
| 3 | Lower Bounds for Locally Private Estimation via Communication Complexity | 2019 | 4 |
| 4 | A Rank-1 Sketch for Matrix Multiplicative Weights | 2019 | 2 |
| 5 | Modeling simple structures and geometry for better stochastic optimization algorithms | 2019 | 2 |
| 6 | Bounds on the conditional and average treatment effect in the presence of unobserved confounders | 2018 | 3 |
| 7 | Generalizing to Unseen Domains via Adversarial Data Augmentation | 2018 | 62 |
| 8 | 2016 | 27 | |
| 9 | Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences | 2016 | 51 |
| 10 | Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care | 2015 | 20 |
| 11 | Minimax rates for memory-bounded sparse linear regression | 2015 | 5 |
| 12 | Information-theoretic lower bounds for distributed statistical estimation with communication constraints | 2014 | 11 |
| 13 | Divide and Conquer Kernel Ridge Regression | 2013 | 68 |
| 14 | Information-theoretic lower bounds for distributed statistical estimation with communication constraints | 2013 | 75 |
| 15 | Estimation, Optimization, and Parallelism when Data is Sparse | 2013 | 27 |
| 16 | Local Privacy and Statistical Minimax Rates | 2013 | 2 |
| 17 | 2013 | 121 | |
| 18 | Oracle inequalities for computationally budgeted model selection | 2011 | 9 |
| 19 | Adaptive Subgradient Methods for Online Learning and Stochastic Optimizationbreakdown → | 2010 | 4936 |
| 20 | On the Consistency of Ranking Algorithms | 2010 | 51 |
About John C. Duchi
John C. Duchi is a scholar working on Statistics and Probability, Management Science and Operations Research, Artificial Intelligence, Numerical Analysis and Computational Mechanics, having authored 80 papers that have together received 8.8k indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (37 papers), Sparse and Compressive Sensing Techniques (25 papers), Advanced Bandit Algorithms Research (15 papers), Machine Learning and Algorithms (14 papers), Statistical Methods and Inference (13 papers), Privacy-Preserving Technologies in Data (13 papers), Advanced Optimization Algorithms Research (8 papers) and Complexity and Algorithms in Graphs (6 papers). The work is most often cited by research in Artificial Intelligence (5.5k citations), Computer Vision and Pattern Recognition (2.0k citations), Computational Mathematics (57 citations), Computational Mechanics (1.5k citations) and Management Science and Operations Research (825 citations). John C. Duchi has collaborated with scholars based in United States, Israel and Sweden. Frequent co-authors include Yoram Singer, Elad Hazan, Martin J. Wainwright, Michael I. Jordan, Shai Shalev‐Shwartz, Tushar Chandra, Alekh Agarwal, Yuchen Zhang, Feng Ruan and Hongseok Namkoong. Their work appears in journals such as SIAM Journal on Optimization, The Annals of Statistics, Journal of Machine Learning Research, IEEE Transactions on Information Theory and Information and Inference A Journal of the IMA.
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.