Inderjit S. Dhillon
About
In The Last Decade
Inderjit S. Dhillon
207 papers receiving 15.6k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Artificial Intelligence 8.4k
- Computer Vision and Pattern Recognition 5.8k
- Statistical and Nonlinear Physics 2.5k
- Signal Processing 2.2k
- Information Systems 1.9k
Countries citing papers authored by Inderjit S. Dhillon
This map shows the geographic impact of Inderjit S. Dhillon'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 Inderjit S. Dhillon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inderjit S. Dhillon more than expected).
Fields of papers citing papers by Inderjit S. Dhillon
This network shows the impact of papers produced by Inderjit S. Dhillon. 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 Inderjit S. Dhillon. The network helps show where Inderjit S. Dhillon may publish in the future.
Co-authorship network of co-authors of Inderjit S. Dhillon
This figure shows the co-authorship network connecting the top 25 collaborators of Inderjit S. Dhillon. A scholar is included among the top collaborators of Inderjit S. Dhillon 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 Inderjit S. Dhillon. Inderjit S. Dhillon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 7 | |
| 3 | DRONE: Data-aware Low-rank Compression for Large NLP Models | 14 |
| 4 | The Limitations of Adversarial Training and the Blind-Spot Attack | 11 |
| 5 | Provable Non-linear Inductive Matrix Completion | 4 |
| 6 | Similarity Preserving Representation Learning for Time Series Analysis. | 8 |
| 7 | Temporal regularized matrix factorization for high-dimensional time series prediction | 215 |
| 8 | PD-sparse: a primal and dual sparse approach to extreme multiclass and multilabel classification | 65 |
| 9 | Optimal classification with multivariate losses | 2 |
| 10 | Mixed Linear Regression with Multiple Components | 7 |
| 11 | Computationally efficient Nyström approximation using fast transforms | 4 |
| 12 | A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models | 3 |
| 13 | Sparse Linear Programming via primal and dual augmented coordinate descent | 10 |
| 14 | 215 | |
| 15 | Large Scale Distributed Sparse Precision Estimation | 17 |
| 16 | Nearest Neighbor based Greedy Coordinate Descent | 22 |
| 17 | Guaranteed Rank Minimization via Singular Value Projection | 240 |
| 18 | Triangle Fixing Algorithms for the Metric Nearness Problem | 4 |
| 19 | 331 | |
| 20 | Application of a New Algorithm for the Symmetric Eigenproblem to Computational Quantum Chemistry. | 12 |
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.