| Decoupled machine learning training S Gupta, B Balaji, LP Dirac, S Genc, V Khare, R Venkatesan, ... US Patent 11,861,490, 2024 | | 2024 |
| Applying compression profiles across similar neural network architectures G Swaminathan, R Venkatesan, Z Xiong, R Luo, V Khare US Patent 11,809,992, 2023 | | 2023 |
| Searching compression profiles for trained neural networks R Venkatesan, G Swaminathan, Z Xiong, R Luo, V Khare US Patent 11,755,603, 2023 | 3 | 2023 |
| Reinforcement learning for training compression policies for machine learning models G Swaminathan, R Venkatesan, Z Xiong, R Luo, V Khare US Patent 11,501,173, 2022 | | 2022 |
| Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks A MacLaughlin, J Dhamala, A Kumar, S Venkatapathy, R Venkatesan, ... arXiv preprint arXiv:2010.04249, 2020 | 5 | 2020 |
| Out-of-the-box channel pruned networks R Venkatesan, G Swaminathan, X Zhou, A Luo arXiv preprint arXiv:2004.14584, 2020 | 2 | 2020 |
| Domain mapping for privacy preservation R Venkatesan, G Swaminathan US Patent 10,567,334, 2020 | 1 | 2020 |
| dsne: Domain adaptation using stochastic neighborhood embedding. X Xu, X Zhou, R Venkatesan, G Swaminathan, O Majumder IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2492-2501, 2019 | 151 | 2019 |
| Feature Extraction and Learning for Visual Data PS Chandakkar, R Venkatesan, B Li, G Dong, Liu, Huang Feature Engineering for Machine Learning and Data Analytics, 55-85, 2018 | 314* | 2018 |
| MIRank-KNN: multiple-instance retrieval of clinically relevant diabetic retinopathy images PS Chandakkar, R Venkatesan, B Li Journal of Medical Imaging 4 (3), 034003-034003, 2017 | 6 | 2017 |
| Convolutional Neural Networks in Visual Computing: A Concise Guide R Venkatesan, B Li CRC Press, Taylor and Francis Group 1, 226, 2017 | 176 | 2017 |
| Convolutional neural networks R Venkatesan, B Li, R Venkatesan, B Li Convolutional Neural Networks in Visual Computing, 89-116, 2017 | 5 | 2017 |
| Novel image representations and learning tasks R Venkatesan Arizona State University, 2017 | 1 | 2017 |
| A strategy for an uncompromising incremental learner R Venkatesan, H Venkateswara, B Li, S Panchanathan arXiv preprint arXiv:1705.00744 3 (6), 2017 | 60 | 2017 |
| Diving deeper into mentee networks R Venkatesan, B Li arXiv preprint arXiv:1604.08220, 2016 | 19 | 2016 |
| On the generality of neural image features R Venkatesan, V Gatupalli, B Li IEEE International Conference on Image Processing, 2016 | 8* | 2016 |
| Trending chic: Analyzing the influence of social media on fashion brands L Manikonda, R Venkatesan, S Kambhampati, B Li arXiv preprint arXiv:1512.01174, 2015 | 46* | 2015 |
| Spatiotemporal video deinterlacing using control grid interpolation R Venkatesan, C Zwart, D Frakes, B Li Journal of Electronic Imaging 24 (2), 043012-043012, 2015 | | 2015 |
| Simpler non-parametric methods provide as good or better results to multiple-instance learning. R Venkatesan, P Chandakkar, B Li IEEE International Conference on Computer Vision, 2015 | 26 | 2015 |
| Exploring Clinically-relevant Image Retrieval for Diabetic Retinopathy Diagnosis B Li, R Venkatesa, P Chandakkar, HK Li, G Chen, S Bernstein AHRQ Grant Final Report, 2014 | | 2014 |
Baoxin LiArizona State UniversityVerified email at asu.edu
