Bamdev Mishra

1.9k total citations
31 papers, 403 citations indexed

About

Bamdev Mishra is a scholar working on Computational Mechanics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Bamdev Mishra has authored 31 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computational Mechanics, 14 papers in Artificial Intelligence and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Bamdev Mishra's work include Sparse and Compressive Sensing Techniques (17 papers), Stochastic Gradient Optimization Techniques (10 papers) and Tensor decomposition and applications (5 papers). Bamdev Mishra is often cited by papers focused on Sparse and Compressive Sensing Techniques (17 papers), Stochastic Gradient Optimization Techniques (10 papers) and Tensor decomposition and applications (5 papers). Bamdev Mishra collaborates with scholars based in Japan, India and United States. Bamdev Mishra's co-authors include Rodolphe Sepulchre, Hiroyuki Kasai, Gilles Meyer, Hiroyuki Sato, Francis Bach, Silvère Bonnabel, Anoop Kunchukuttan, Junbin Gao, Xia Hong and Baocai Yin and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Wireless Communications and Machine Learning.

In The Last Decade

Bamdev Mishra

28 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bamdev Mishra Japan	10	221	136	130	91	53	31	403
Luis Rademacher United States	7	180 0.8×	193 1.4×	98 0.8×	44 0.5×	29 0.5×	26	401
Matus Telgarsky United States	7	121 0.5×	223 1.6×	54 0.4×	211 2.3×	14 0.3×	15	469
Kim Batselier Hong Kong	14	153 0.7×	87 0.6×	48 0.4×	212 2.3×	36 0.7×	51	457
Venkat Chandrasekaran United States	11	214 1.0×	184 1.4×	82 0.6×	19 0.2×	83 1.6×	27	589
Chris Peterson United States	14	97 0.4×	79 0.6×	103 0.8×	97 1.1×	30 0.6×	62	592
Chunfeng Cui China	12	74 0.3×	41 0.3×	45 0.3×	158 1.7×	33 0.6×	39	394
Max Simchowitz United States	6	148 0.7×	140 1.0×	69 0.5×	11 0.1×	52 1.0×	18	326
Guang‐Jing Song China	14	197 0.9×	38 0.3×	179 1.4×	203 2.2×	66 1.2×	43	716
Berkant Savas Sweden	10	151 0.7×	140 1.0×	85 0.7×	282 3.1×	32 0.6×	19	531
Minru Bai China	14	243 1.1×	20 0.1×	192 1.5×	221 2.4×	48 0.9×	32	485

Countries citing papers authored by Bamdev Mishra

Since Specialization

Citations

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

Fields of papers citing papers by Bamdev Mishra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bamdev Mishra

This figure shows the co-authorship network connecting the top 25 collaborators of Bamdev Mishra. A scholar is included among the top collaborators of Bamdev Mishra 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 Bamdev Mishra. Bamdev Mishra 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

Mishra, Bamdev, et al.. (2025). A Riemannian Approach to Ground Metric Learning for Optimal Transport. 1–5.

Kumar, Pawan, et al.. (2024). A Gauss-Newton Approach for Min-Max Optimization in Generative Adversarial Networks. 1–9.

Mishra, Bamdev, et al.. (2023). Riemannian Hamiltonian Methods for Min-Max Optimization on Manifolds. SIAM Journal on Optimization. 33(3). 1797–1827. 3 indexed citations

Mishra, Bamdev, et al.. (2023). Light-weight Deep Extreme Multilabel Classification. 42. 1–8. 1 indexed citations

Mishra, Bamdev, et al.. (2022). Riemannian block SPD coupling manifold and its application to optimal transport. Machine Learning. 113(4). 1595–1622. 2 indexed citations

Mishra, Bamdev, et al.. (2021). Efficient Robust Optimal Transport with Application to Multi-Label Classification. 2021 60th IEEE Conference on Decision and Control (CDC). 1490–1495. 2 indexed citations

Kasai, Hiroyuki, et al.. (2019). Riemannian adaptive stochastic gradient algorithms on matrix manifolds. International Conference on Machine Learning. 3262–3271. 3 indexed citations

Kunchukuttan, Anoop, et al.. (2019). Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach. Transactions of the Association for Computational Linguistics. 7. 107–120. 39 indexed citations

Sato, Hiroyuki, Hiroyuki Kasai, & Bamdev Mishra. (2019). Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport. SIAM Journal on Optimization. 29(2). 1444–1472. 32 indexed citations

10.

Kasai, Hiroyuki, Hiroyuki Sato, & Bamdev Mishra. (2018). Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis.. International Conference on Machine Learning. 2521–2529. 1 indexed citations

11.

Kasai, Hiroyuki, Hiroyuki Sato, & Bamdev Mishra. (2018). Riemannian Stochastic Recursive Gradient Algorithm. International Conference on Machine Learning. 2516–2524. 13 indexed citations

12.

Nimishakavi, Madhav, et al.. (2018). A Dual Framework for Low-rank Tensor Completion. NOT FOUND REPOSITORY (Indian Institute of Science Bangalore). 31. 5484–5495. 4 indexed citations

13.

Kasai, Hiroyuki & Bamdev Mishra. (2018). Inexact trust-region algorithms on Riemannian manifolds. Neural Information Processing Systems. 31. 4249–4260. 7 indexed citations

14.

Kasai, Hiroyuki & Bamdev Mishra. (2018). Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifolds. 2010–2014. 2 indexed citations

15.

Nimishakavi, Madhav, et al.. (2017). A dual framework for trace norm regularized low-rank tensor completion. arXiv (Cornell University). 1 indexed citations

16.

Sato, Hiroyuki, Hiroyuki Kasai, & Bamdev Mishra. (2017). Riemannian stochastic variance reduced gradient. arXiv (Cornell University). 6 indexed citations

17.

Mishra, Bamdev, et al.. (2017). A Unified Framework for Structured Low-rank Matrix Learning. arXiv (Cornell University). 2254–2263. 3 indexed citations

18.

Kasai, Hiroyuki & Bamdev Mishra. (2016). Low-rank tensor completion: a Riemannian manifold preconditioning approach. 1012–1021. 34 indexed citations

19.

Kasai, Hiroyuki & Bamdev Mishra. (2015). Riemannian preconditioning for tensor completion. IEICE Technical Report; IEICE Tech. Rep.. 115(436). 55–60. 1 indexed citations

20.

Mishra, Bamdev. (2014). A Riemannian approach to large-scale constrained least-squares with symmetries. Open Repository and Bibliography (University of Liège). 5 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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