| Intime: A machine learning approach for efficient selection of fpga cad tool parameters N Kapre, H Ng, K Teo, J Naude Proceedings of the 2015 ACM/SIGDA International Symposium on Field …, 2015 | 48 | 2015 |
| Driving timing convergence of FPGA designs through machine learning and cloud computing N Kapre, B Chandrashekaran, H Ng, K Teo 2015 IEEE 23rd Annual International Symposium on Field-Programmable Custom …, 2015 | 44 | 2015 |
| Improving classification accuracy of a machine learning approach for fpga timing closure Q Yanghua, N Kapre, H Ng, K Teo 2016 IEEE 24th Annual International Symposium on Field-Programmable Custom …, 2016 | 21 | 2016 |
| Case for design-specific machine learning in timing closure of FPGA designs Q Yanghua, C Adaikkala Raj, H Ng, K Teo, N Kapre Proceedings of the 2016 ACM/SIGDA International Symposium on Field …, 2016 | 10 | 2016 |
| Machine Learning-based Smart Assessment of User Floorplan Quality without running Place & Route HH Ng, K Teo | | |
