Garvesh Raskutti

3.7k total citations
41 papers, 1.8k citations indexed

About

Garvesh Raskutti is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Garvesh Raskutti has authored 41 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Statistics and Probability, 15 papers in Artificial Intelligence and 12 papers in Computational Mechanics. Recurrent topics in Garvesh Raskutti's work include Statistical Methods and Inference (21 papers), Sparse and Compressive Sensing Techniques (12 papers) and Bayesian Modeling and Causal Inference (5 papers). Garvesh Raskutti is often cited by papers focused on Statistical Methods and Inference (21 papers), Sparse and Compressive Sensing Techniques (12 papers) and Bayesian Modeling and Causal Inference (5 papers). Garvesh Raskutti collaborates with scholars based in United States, Australia and Hong Kong. Garvesh Raskutti's co-authors include Martin J. Wainwright, Bin Yu, Pradeep Ravikumar, Bin Yu, Caroline Uhler, Kerry Hinton, Rebecca Willett, Rodney S. Tucker, Bin Yu and Peter Bühlmann and has published in prestigious journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Information Theory.

In The Last Decade

Garvesh Raskutti

40 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Garvesh Raskutti United States 19 686 667 447 165 160 41 1.8k
Malik Magdon‐Ismail United States 26 104 0.2× 896 1.3× 332 0.7× 204 1.2× 97 0.6× 133 2.4k
Pradeep Ravikumar United States 29 598 0.9× 2.5k 3.7× 614 1.4× 52 0.3× 424 2.6× 103 4.0k
Rie Johnson United States 10 105 0.2× 1.8k 2.7× 421 0.9× 85 0.5× 128 0.8× 12 2.3k
Le Song United States 26 110 0.2× 1.0k 1.5× 96 0.2× 145 0.9× 654 4.1× 77 2.9k
Immanuel M. Bomze Austria 28 57 0.1× 343 0.5× 300 0.7× 196 1.2× 136 0.8× 115 2.8k
Alessandro Rinaldo United States 20 567 0.8× 565 0.8× 103 0.2× 39 0.2× 139 0.9× 57 1.5k
Vladimir Spokoiny Germany 25 1.3k 1.8× 679 1.0× 310 0.7× 66 0.4× 90 0.6× 107 2.7k
Cédric Archambeau United Kingdom 19 145 0.2× 606 0.9× 72 0.2× 49 0.3× 150 0.9× 49 1.1k
Zhaosong Lu Canada 26 294 0.4× 500 0.7× 1.1k 2.4× 90 0.5× 91 0.6× 69 2.0k

Countries citing papers authored by Garvesh Raskutti

Since Specialization
Citations

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

Fields of papers citing papers by Garvesh Raskutti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Garvesh Raskutti

This figure shows the co-authorship network connecting the top 25 collaborators of Garvesh Raskutti. A scholar is included among the top collaborators of Garvesh Raskutti 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 Garvesh Raskutti. Garvesh Raskutti 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.
Kontar, Raed Al, Eunshin Byon, Mosharaf Chowdhury, et al.. (2021). The Internet of Federated Things (IoFT). IEEE Access. 9. 156071–156113. 37 indexed citations
2.
Raskutti, Garvesh, et al.. (2021). Prediction in the Presence of Response-Dependent Missing Labels. ScholarSphere (Penn State Libraries). 32. 451–455. 1 indexed citations
3.
Chen, Hao, et al.. (2020). Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes. Neural Information Processing Systems. 33. 2722–2733. 8 indexed citations
4.
Kontar, Raed Al, Garvesh Raskutti, & Shiyu Zhou. (2020). Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(10). 3508–3522. 19 indexed citations
5.
Raskutti, Garvesh, et al.. (2020). Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning. Cell Systems. 12(1). 92–101.e8. 31 indexed citations
6.
Raskutti, Garvesh & Caroline Uhler. (2018). Learning directed acyclic graph models based on sparsest permutations. Stat. 7(1). 21 indexed citations
7.
Raskutti, Garvesh, et al.. (2018). Minimax Optimal Convex Methods for Poisson Inverse Problems Under <inline-formula> <tex-math notation="LaTeX">$\ell_{q}$ </tex-math> </inline-formula>-Ball Sparsity. IEEE Transactions on Information Theory. 64(8). 5498–5512. 7 indexed citations
8.
Wang, Si, Weihong Guo, Ting‐Zhu Huang, & Garvesh Raskutti. (2016). Image inpainting using reproducing kernel Hilbert space and Heaviside functions. Journal of Computational and Applied Mathematics. 311. 551–564. 6 indexed citations
9.
Forster, Marc R., et al.. (2016). The Frugal Inference of Causal Relations. The British Journal for the Philosophy of Science. 69(3). 821–848. 14 indexed citations
10.
Raskutti, Garvesh & Michael W. Mahoney. (2015). Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares. International Conference on Machine Learning. 617–625. 7 indexed citations
11.
Raskutti, Garvesh, et al.. (2015). Learning large-scale Poisson DAG models based on overdispersion scoring. Neural Information Processing Systems. 28. 631–639. 8 indexed citations
12.
Raskutti, Garvesh, Martin J. Wainwright, & Bin Yu. (2012). Minimax-optimal rates for sparse additive models over kernel classes via convex programming. Journal of Machine Learning Research. 13(1). 389–427. 111 indexed citations
13.
Ravikumar, Pradeep, Martin J. Wainwright, Garvesh Raskutti, & Bin Yu. (2011). High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence. Electronic Journal of Statistics. 5(none). 392 indexed citations
14.
Raskutti, Garvesh, Martin J. Wainwright, & Bin Yu. (2010). Restricted Eigenvalue Properties for Correlated Gaussian Designs. Journal of Machine Learning Research. 11(78). 2241–2259. 189 indexed citations
15.
Raskutti, Garvesh, Bin Yu, & Martin J. Wainwright. (2009). Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness. Neural Information Processing Systems. 22. 1563–1570. 8 indexed citations
16.
Wong, Eric W. M., Jayant Baliga, Moshe Zukerman, Andrew Zalesky, & Garvesh Raskutti. (2009). A New Method for Blocking Probability Evaluation in OBS/OPS Networks With Deflection Routing. Journal of Lightwave Technology. 27(23). 5335–5347. 28 indexed citations
17.
Raskutti, Garvesh, Bin Yu, Martin J. Wainwright, & Pradeep Ravikumar. (2008). Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of boldmathell_1-regularized MLE. Neural Information Processing Systems. 21. 1329–1336. 55 indexed citations
18.
Tucker, R.S., Kerry Hinton, & Garvesh Raskutti. (2007). Energy consumption limits in high-speed optical and electronic signal processing. Electronics Letters. 43(17). 906–908. 14 indexed citations
19.
Raskutti, Garvesh, Andrew Zalesky, Eric W. M. Wong, & Moshe Zukerman. (2007). Enhanced Blocking Probability Evaluation Method for Circuit-Switched Trunk Reservation Networks. IEEE Communications Letters. 11(6). 543–545. 15 indexed citations
20.
Duong, Cuong, Danielle Greenawalt, Adam Kowalczyk, et al.. (2007). Pretreatment Gene Expression Profiles Can Be Used to Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer. Annals of Surgical Oncology. 14(12). 3602–3609. 52 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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