Daniel Hsu
Impact in
- Computational Mathematics top 0.2%
- Tensor decomposition and applications
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms
- Machine Learning and Data Classification
- Text and Document Classification Technologies
- Topic Modeling
Papers in
-
- Machine Learning and Algorithms 24
- Bayesian Methods and Mixture Models 9
- Privacy-Preserving Technologies in Data 7
- Gaussian Processes and Bayesian Inference 7
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- Statistical Methods and Inference 15
- Co-authors
- Sham M. Kakade (20 shared papers)Mikhail Belkin (3 shared papers)Siyuan Ma (2 shared papers)Soumik Mandal (2 shared papers)Sanjoy Dasgupta (4 shared papers)Animashree Anandkumar (5 shared papers)Rong Ge (3 shared papers)Miguel Figueroa (6 shared papers)
- Journals
- Journal of Machine Learning Research (4 papers)Physical review. D (3 papers)IEEE Journal of Solid-State Circuits (2 papers)Electronic Communications in Probability (2 papers)Transactions of the Association for Computational Linguistics (2 papers)
- Partner nations
- United StatesUnited KingdomSingapore
In The Last Decade
Daniel Hsu
83 papers receiving 3.7k citations
Daniel Hsu's Hit Papers
Peers
Comparison fields: 5 of 178
- Computational Mathematics 360
- Artificial Intelligence 2.0k
- Statistics and Probability 333
- Computer Vision and Pattern Recognition 709
- Signal Processing 343
Countries citing papers authored by Daniel Hsu
This map shows the geographic impact of Daniel Hsu'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 Daniel Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Hsu more than expected).
Fields of papers citing papers by Daniel Hsu
This network shows the impact of papers produced by Daniel Hsu. 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 Daniel Hsu. The network helps show where Daniel Hsu may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Hsu, 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 85 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reconciling modern machine-learning practice and the classical bias–variance trade-off Hit paper breakdown → | 2019 | 716 |
| 2 | Tensor decompositions for learning latent variable models Hit paper breakdown → | 2014 | 378 |
| 3 | 2008 | 277 | |
| 4 | 2002 | 234 | |
| 5 | Multi-Label Prediction via Compressed Sensing | 2009 | 186 |
| 6 | 2004 | 156 | |
| 7 | 2012 | 144 | |
| 8 | 2011 | 123 | |
| 9 | 2014 | 109 | |
| 10 | 2013 | 98 | |
| 11 | 2012 | 88 | |
| 12 | 2018 | 81 | |
| 13 | 2014 | 72 | |
| 14 | 2008 | 71 | |
| 15 | 2019 | 70 | |
| 16 | 2009 | 60 | |
| 17 | 2020 | 57 | |
| 18 | 2014 | 53 | |
| 19 | 2014 | 48 | |
| 20 | What makes some POMDP problems easy to approximate | 2007 | 47 |
About Daniel Hsu
Daniel Hsu is a scholar working on Artificial Intelligence, Statistics and Probability, Computational Mechanics, Signal Processing and Computational Mathematics, having authored 85 papers that have together received 3.9k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (24 papers), Statistical Methods and Inference (15 papers), Sparse and Compressive Sensing Techniques (14 papers), Blind Source Separation Techniques (11 papers), Bayesian Methods and Mixture Models (9 papers), Tensor decomposition and applications (8 papers), Privacy-Preserving Technologies in Data (7 papers) and Gaussian Processes and Bayesian Inference (7 papers). The work is most often cited by research in Computational Mathematics (360 citations), Artificial Intelligence (2.0k citations), Statistics and Probability (333 citations), Computer Vision and Pattern Recognition (709 citations) and Signal Processing (343 citations). Daniel Hsu has collaborated with scholars based in United States, United Kingdom and Singapore. Frequent co-authors include Sham M. Kakade, Mikhail Belkin, Siyuan Ma, Soumik Mandal, Sanjoy Dasgupta, Animashree Anandkumar, Rong Ge, Miguel Figueroa, C. Diorio and Matus Telgarsky. Their work appears in journals such as Journal of Machine Learning Research, Physical review. D, IEEE Journal of Solid-State Circuits, Electronic Communications in Probability and Transactions 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.