Partha Niyogi
- Computer Vision and Pattern Recognition top 0.02%
- Artificial Intelligence top 0.05%
- Media Technology top 0.05%
- Computational Mechanics top 0.2%
- Signal Processing top 0.1%
- Co-authors
- Mikhail BelkinXiaofei HeVikas SindhwaniDeng CaiShuicheng YanHao ZhangYuxiao HuFederico Girosi
- Topics
- Speech and Audio Processing (18 papers)Face and Expression Recognition (18 papers)Machine Learning and Algorithms (15 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Partha Niyogi
82 papers receiving 18.9k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Computer Vision and Pattern Recognition 11.1k
- Artificial Intelligence 7.9k
- Media Technology 2.5k
- Computational Mechanics 2.3k
- Signal Processing 2.2k
Countries citing papers authored by Partha Niyogi
This map shows the geographic impact of Partha Niyogi'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 Partha Niyogi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Partha Niyogi more than expected).
Fields of papers citing papers by Partha Niyogi
This network shows the impact of papers produced by Partha Niyogi. 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 Partha Niyogi. The network helps show where Partha Niyogi may publish in the future.
Co-authorship network of co-authors of Partha Niyogi
This figure shows the co-authorship network connecting the top 25 collaborators of Partha Niyogi. A scholar is included among the top collaborators of Partha Niyogi 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 Partha Niyogi. Partha Niyogi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Manifold regularization and semi-supervised learning: some theoretical analyses | 58 |
| 2 | Combining Data and Mathematical Models of Language Change | 4 |
| 3 | Generalization Bounds for Ranking Algorithms via Algorithmic Stability | 95 |
| 4 | On the sample complexity of learning smooth cuts on a manifold | 4 |
| 5 | Multiview point cloud kernels for semisupervised learning | 3 |
| 6 | 4 | |
| 7 | 273 | |
| 8 | Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examplesbreakdown → | 2271 |
| 9 | Laplacian Score for Feature Selectionbreakdown → | 1321 |
| 10 | On Manifold Regularization. | 243 |
| 11 | Tensor Subspace Analysis | 276 |
| 12 | 173 | |
| 13 | Locality Preserving Projectionsbreakdown → | 2932 |
| 14 | 29 | |
| 15 | Using manifold structure for partially labelled classification | 63 |
| 16 | Using Manifold Stucture for Partially Labeled Classification | 43 |
| 17 | Feature based representation for audio-visual speech recognition. | 12 |
| 18 | Learning from triggers | 27 |
| 19 | Active Learning for Function Approximation | 19 |
| 20 | Modelling Speaker Variability and Imposing Speaker Constraints in Phonetic Classification | 1 |
About Partha Niyogi
Partha Niyogi is a scholar working on Signal Processing, Artificial Intelligence and Cultural Studies, having authored 83 papers that have together received 19.8k indexed citations. Recurring topics across this work include Speech and Audio Processing (18 papers), Face and Expression Recognition (18 papers) and Machine Learning and Algorithms (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (11.1k citations), Computational Mathematics (211 citations) and Media Technology (2.5k citations). Partha Niyogi has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Mikhail Belkin, Xiaofei He, Vikas Sindhwani, Deng Cai, Shuicheng Yan, Hao Zhang, Yuxiao Hu, Xiaofei He, Federico Girosi and Tomaso Poggio. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.