| Optimizing top precision performance measure of content-based image retrieval by learning similarity function RZ Liang, L Shi, H Wang, J Meng, JJY Wang, Q Sun, Y Gu 2016 23rd International conference on pattern recognition (ICPR), 2954-2958, 2016 | 106 | 2016 |
| Predict the click-through rate and average cost per click for keywords using machine learning methodologies L Shi, B Li Proceedings of the International Conference on Industrial Engineering and …, 2016 | 21 | 2016 |
| A new variable sampling control scheme at fixed times for monitoring the process dispersion L Shi, C Zou, Z Wang, KC Kapur Quality and Reliability Engineering International 25 (8), 961-972, 2009 | 21 | 2009 |
| Methods and automated systems for testing, optimization, and analysis that use robust statistical processing of non-binomial experimental results V Brayman, L Shi, S Wood US Patent 9,460,135, 2016 | 16 | 2016 |
| A synthesis of feedback and feedforward control for process improvement under stationary and nonstationary time series disturbance models L Shi, KC Kapur Quality and Reliability Engineering International 31 (3), 343-354, 2015 | 10 | 2015 |
| Process monitoring and feedforward control for proactive quality improvement LSHIKC KAPUR International Journal of Performability Engineering 8 (6), 601, 2012 | 3 | 2012 |
| Quasi-feedforward and feedback control for random step shift disturbance models L Shi, KC Kapur Quality Technology & Quantitative Management 12 (1), 69-82, 2015 | 2 | 2015 |
| Semi-supervised structured output prediction by local linear regression and sub-gradient descent Y Zhou, J Wang, L Shi, H Wang, X Du, G Silva arXiv preprint arXiv:1606.02279, 2016 | | 2016 |
| Feedforward Control and Process Improvement for Some Time Series Disturbance Models L Shi University of Washington, 2012 | | 2012 |
| Process Adjustment and Feedforward Control L Shi, KC Kapur IIE Annual Conference. Proceedings, 1, 2010 | | 2010 |
