Daniel P. Robinson

2.5k total citations · 1 hit paper
66 papers, 1.3k citations indexed

About

Daniel P. Robinson is a scholar working on Numerical Analysis, Computational Mechanics and Computational Theory and Mathematics. According to data from OpenAlex, Daniel P. Robinson has authored 66 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Numerical Analysis, 30 papers in Computational Mechanics and 30 papers in Computational Theory and Mathematics. Recurrent topics in Daniel P. Robinson's work include Advanced Optimization Algorithms Research (38 papers), Sparse and Compressive Sensing Techniques (28 papers) and Stochastic Gradient Optimization Techniques (14 papers). Daniel P. Robinson is often cited by papers focused on Advanced Optimization Algorithms Research (38 papers), Sparse and Compressive Sensing Techniques (28 papers) and Stochastic Gradient Optimization Techniques (14 papers). Daniel P. Robinson collaborates with scholars based in United States, United Kingdom and China. Daniel P. Robinson's co-authors include Renè Vidal, Chong You, Frank E. Curtis, Nicholas I. M. Gould, Philip E. Gill, Chun-Guang Li, Vyacheslav Kungurtsev, Hao Jiang, Zheng Han and Albert S. Berahas and has published in prestigious journals such as IEEE Transactions on Automatic Control, Journal of Medicinal Chemistry and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Daniel P. Robinson

65 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit

2016 243 citations Chong You, Daniel P. Robinson et al. profile →

Peers

Daniel P. Robinson

NA

CM

CVPR

AI

CTM

François Glineur Belgium

Ting Kei Pong Hong Kong

Zhi-Quan Luo United States

Nicolas Gillis Belgium

Jiming Peng United States

Houduo Qi United Kingdom

Deren Han China

Chunpeng Wang China

Jesse L. Barlow United States

Xudong Li China

François Glineur Belgium

Daniel P. Robinson

335 ×0.7

NA

467 ×1.0

CM

196 ×0.5

CVPR

383 ×1.0

AI

253 ×0.7

CTM

Citations per year, relative to Daniel P. Robinson Daniel P. Robinson (= 1×) peers François Glineur

Countries citing papers authored by Daniel P. Robinson

Since Specialization

Citations

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

Fields of papers citing papers by Daniel P. Robinson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel P. Robinson. 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 P. Robinson. The network helps show where Daniel P. Robinson may publish in the future.

Co-authorship network of co-authors of Daniel P. Robinson

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel P. Robinson. A scholar is included among the top collaborators of Daniel P. Robinson 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 Daniel P. Robinson. Daniel P. Robinson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Banbury, Colby, et al.. (2025). Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression. 15234–15244.

2.

Curtis, Frank E., et al.. (2024). Sequential Quadratic Optimization for Stochastic Optimization with Deterministic Nonlinear Inequality and Equality Constraints. SIAM Journal on Optimization. 34(4). 3592–3622. 2 indexed citations

3.

Robinson, Daniel P., et al.. (2023). A Nonsmooth Dynamical Systems Perspective on Accelerated Extensions of ADMM. IEEE Transactions on Automatic Control. 68(5). 2966–2978. 6 indexed citations

4.

Curtis, Frank E., Suyun Liu, & Daniel P. Robinson. (2023). Fair machine learning through constrained stochastic optimization and an $$\epsilon$$-constraint method. Optimization Letters. 18(9). 1975–1991. 1 indexed citations

5.

Ding, Tianyu, Zhihui Zhu, Manolis C. Tsakiris, Renè Vidal, & Daniel P. Robinson. (2021). Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms. International Conference on Artificial Intelligence and Statistics. 2944–2952. 3 indexed citations

6.

Prati, Federica, et al.. (2019). Virtual Screening Approach and Investigation of Structure–Activity Relationships To Discover Novel Bacterial Topoisomerase Inhibitors Targeting Gram-Positive and Gram-Negative Pathogens. Journal of Medicinal Chemistry. 62(16). 7445–7472. 13 indexed citations

7.

Zhu, Zhihui, et al.. (2019). A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning. Neural Information Processing Systems. 32. 9437–9447. 6 indexed citations

8.

Zhu, Zhihui, et al.. (2019). Noisy Dual Principal Component Pursuit. International Conference on Machine Learning. 1617–1625. 7 indexed citations

9.

Curtis, Frank E., et al.. (2019). Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees\n for Nonconvex Optimization. arXiv (Cornell University). 18 indexed citations

10.

Behera, Ardhendu, et al.. (2019). A CNN Model for Head Pose Recognition using Wholes and Regions. Edge Hill University Research Information Repository (Edge Hill University). 91. 1–2. 7 indexed citations

11.

You, Chong, Chi Li, Daniel P. Robinson, & Renè Vidal. (2018). Scalable Exemplar-based Subspace Clustering on Class-Imbalanced Data. 67–83. 15 indexed citations

12.

Robinson, Daniel P., et al.. (2018). Relax, and Accelerate: A Continuous Perspective on ADMM. arXiv (Cornell University). 1 indexed citations

13.

Zhu, Zhihui, Yifan Wang, Daniel P. Robinson, et al.. (2018). Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms. Neural Information Processing Systems. 31. 2171–2181. 10 indexed citations

14.

Chen, Tianyi, Frank E. Curtis, & Daniel P. Robinson. (2017). A Reduced-Space Algorithm for Minimizing $\ell_1$-Regularized Convex Functions. SIAM Journal on Optimization. 27(3). 1583–1610. 11 indexed citations

15.

Curtis, Frank E., Nicholas I. M. Gould, Daniel P. Robinson, & Philippe L. Toint. (2016). An interior-point trust-funnel algorithm for nonlinear optimization. Science and Technology Facilities Council. 11 indexed citations

16.

You, Chong, Daniel P. Robinson, & Renè Vidal. (2016). Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. 3918–3927. 243 indexed citations breakdown →

17.

Robinson, Daniel P., et al.. (2015). Sparse Subspace Clustering with Missing Entries. International Conference on Machine Learning. 2463–2472. 41 indexed citations

18.

Gould, Nicholas I. M. & Daniel P. Robinson. (2010). A Second Derivative SQP Method: Local Convergence and Practical Issues. SIAM Journal on Optimization. 20(4). 2049–2079. 25 indexed citations

19.

Revill, W. Peter, Jan Voda, Loleta Chung, et al.. (2002). Genetically Engineered Analogs of Ascomycin for Nerve Regeneration. Journal of Pharmacology and Experimental Therapeutics. 302(3). 1278–1285. 41 indexed citations

20.

Robinson, Daniel P.. (2000). Madness, Badness, and Fitness: Law and Psychiatry (Again). Project Muse (Johns Hopkins University). 2 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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