Rashish Tandon

498 total citations
5 papers, 248 citations indexed

About

Rashish Tandon is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Networks and Communications. According to data from OpenAlex, Rashish Tandon has authored 5 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Statistics and Probability and 1 paper in Computer Networks and Communications. Recurrent topics in Rashish Tandon's work include Bayesian Modeling and Causal Inference (2 papers), Machine Learning and Algorithms (2 papers) and IoT and Edge/Fog Computing (1 paper). Rashish Tandon is often cited by papers focused on Bayesian Modeling and Causal Inference (2 papers), Machine Learning and Algorithms (2 papers) and IoT and Edge/Fog Computing (1 paper). Rashish Tandon collaborates with scholars based in United States and United Kingdom. Rashish Tandon's co-authors include Alexandros G. Dimakis, Qi Lei, Nikos Karampatziakis, Pradeep Ravikumar, Animashree Anandkumar, Prateek Jain, Alekh Agarwal, Praneeth Netrapalli and Karthikeyan Shanmugam and has published in prestigious journals such as Neural Information Processing Systems, International Conference on Machine Learning and Conference on Learning Theory.

In The Last Decade

Rashish Tandon

5 papers receiving 243 citations

Peers

Rashish Tandon
Rashish Tandon
Citations per year, relative to Rashish Tandon Rashish Tandon (= 1×) peers Toshiyasu Matsushima

Countries citing papers authored by Rashish Tandon

Since Specialization
Citations

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

Fields of papers citing papers by Rashish Tandon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rashish Tandon

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

All Works

5 of 5 papers shown
1.
Tandon, Rashish, Qi Lei, Alexandros G. Dimakis, & Nikos Karampatziakis. (2017). Gradient Coding: Avoiding Stragglers in Distributed Learning. International Conference on Machine Learning. 3368–3376. 196 indexed citations
2.
Agarwal, Alekh, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, & Rashish Tandon. (2014). Learning Sparsely Used Overcomplete Dictionaries. Conference on Learning Theory. 123–137. 28 indexed citations
3.
Tandon, Rashish & Pradeep Ravikumar. (2014). Learning Graphs with a Few Hubs. International Conference on Machine Learning. 602–610. 3 indexed citations
4.
Tandon, Rashish, Karthikeyan Shanmugam, Pradeep Ravikumar, & Alexandros G. Dimakis. (2014). On the Information Theoretic Limits of Learning Ising Models. Neural Information Processing Systems. 27. 2303–2311. 9 indexed citations
5.
Tandon, Rashish & Pradeep Ravikumar. (2013). On the difficulty of learning power law graphical models. 2493–2497. 12 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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