| Mvg mechanism: Differential privacy under matrix-valued query T Chanyaswad, A Dytso, HV Poor, P Mittal Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 55 | 2018 |
| Investigating statistical privacy frameworks from the perspective of hypothesis testing C Liu, X He, T Chanyaswad, S Wang, P Mittal Proceedings on Privacy Enhancing Technologies, 2019 | 41 | 2019 |
| A compressive multi-kernel method for privacy-preserving machine learning T Chanyaswad, JM Chang, SY Kung 2017 International Joint Conference on Neural Networks (IJCNN), 4079-4086, 2017 | 33 | 2017 |
| Collaborative PCA/DCA learning methods for compressive privacy SY Kung, T Chanyaswad, JM Chang, P Wu ACM Transactions on Embedded Computing Systems (TECS) 16 (3), 1-18, 2017 | 28 | 2017 |
| Ron-gauss: Enhancing utility in non-interactive private data release T Chanyaswad, C Liu, P Mittal arXiv preprint arXiv:1709.00054, 2017 | 26 | 2017 |
| Discriminant-component eigenfaces for privacy-preserving face recognition T Chanyaswad, JM Chang, P Mittal, SY Kung 2016 IEEE 26th International Workshop on Machine Learning for Signal …, 2016 | 19 | 2016 |
| Multi-kernel, deep neural network and hybrid models for privacy preserving machine learning M Al, T Chanyaswad, SY Kung 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 12 | 2018 |
| Coupling dimensionality reduction with generative model for non-interactive private data release T Chanyaswad, C Liu, P Mittal arXiv preprint arXiv:1709.00054, 2017 | 7 | 2017 |
| Differential mutual information forward search for multi-kernel discriminant-component selection with an application to privacy-preserving classification T Chanyaswad, M Al, JM Chang, SY Kung 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | 6 | 2017 |
| Outlier Removal for Enhancing Kernel-Based Classifier Via the Discriminant Information T Chanyaswad, M Al, SY Kung 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 2 | 2018 |
| A Differential Privacy Mechanism Design Under Matrix-Valued Query T Chanyaswad, A Dytso, HV Poor, P Mittal arXiv preprint arXiv:1802.10077, 2018 | 1 | 2018 |
| Privacy-Preserving Machine Learning via Data Compression & Differential Privacy T Chanyaswad Princeton University, 2018 | 1 | 2018 |
| Desensitized RDCA Subspaces for Compressive Privacy in Machine Learning A Filipowicz, T Chanyaswad, SY Kung arXiv preprint arXiv:1707.07770, 2017 | 1 | 2017 |
| A biomolecular implementation of systems described by linear and nonlinear ODE’s VV Kulkarni, H Jiang, T Chanyaswad, M Riedel Proc. Int. Workshop Biodesign Autom, 40-41, 2013 | 1 | 2013 |
| Supervising Nystr\" om Methods via Negative Margin Support Vector Selection M Al, T Chanyaswad, SY Kung arXiv preprint arXiv:1805.04018, 2018 | | 2018 |
| Robust tunable in vitro transcriptional oscillator networks VV Kulkarni, T Chanyaswad, M Riedel, J Kim 2012 50th Annual Allerton Conference on Communication, Control, and …, 2012 | | 2012 |
| Networks of Synthetic Biological Oscillators T Chanyaswad | | 2012 |
| Robust Tunable Synthetic Biological Oscillator Networks VV Kulkarni, T Chanyaswad, M Riedel, J Kim | | |
Sun-Yuan KungProfessor of Electrical Engineering, Princeton UniversityE-mail confirmado em princeton.edu