| SATzilla: portfolio-based algorithm selection for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown Journal of Artificial Intelligence Research 32 (1), 565-606, 2008 | 1047 | 2008 |
| Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014 | 480 | 2014 |
| Fault diagnosis for rotating machinery using multiple sensors and convolutional neural networks M Xia, T Li, L Xu, L Liu, CW De Silva IEEE/ASME transactions on mechatronics 23 (1), 101-110, 2017 | 476 | 2017 |
| Hydra: Automatically configuring algorithms for portfolio-based selection L Xu, H Hoos, K Leyton-Brown Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 210-216, 2010 | 221 | 2010 |
| SATenstein: Automatically building local search SAT solvers from components AR KhudaBukhsh, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 232, 20-42, 2016 | 211 | 2016 |
| SATzilla-07: The design and analysis of an algorithm portfolio for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown Principles and Practice of Constraint Programming–CP 2007: 13th …, 2007 | 167 | 2007 |
| Evaluating component solver contributions to portfolio-based algorithm selectors L Xu, F Hutter, H Hoos, K Leyton-Brown Theory and Applications of Satisfiability Testing–SAT 2012: 15th …, 2012 | 124 | 2012 |
| Hydra-MIP: Automated algorithm configuration and selection for mixed integer programming L Xu, F Hutter, HH Hoos, K Leyton-Brown RCRA workshop on experimental evaluation of algorithms for solving problems …, 2011 | 119 | 2011 |
| A new efficient algorithm for solving the simple temporal problem L Xu, BY Choueiry | 110 | 2003 |
| SATzilla2012: Improved algorithm selection based on cost-sensitive classification models L Xu, F Hutter, J Shen, HH Hoos, K Leyton-Brown Proceedings of SAT Challenge, 57-58, 2012 | 105 | 2012 |
| Intelligent fault diagnosis approach with unsupervised feature learning by stacked denoising autoencoder M Xia, T Li, L Liu, L Xu, CW de Silva IET Science, Measurement & Technology 11 (6), 687-695, 2017 | 99 | 2017 |
| SATzilla2009: an automatic algorithm portfolio for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown SAT 4, 53-55, 2009 | 70 | 2009 |
| Hierarchical hardness models for SAT L Xu, HH Hoos, K Leyton-Brown Principles and Practice of Constraint Programming–CP 2007: 13th …, 2007 | 64 | 2007 |
| Understanding the empirical hardness of NP-complete problems K Leyton-Brown, HH Hoos, F Hutter, L Xu Communications of the ACM 57 (5), 98-107, 2014 | 52 | 2014 |
| Predicting satisfiability at the phase transition L Xu, H Hoos, K Leyton-Brown Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 584-590, 2012 | 28 | 2012 |
| Colorectal cancer detection based on deep learning L Xu, B Walker, PI Liang, Y Tong, C Xu, YC Su, A Karsan Journal of Pathology Informatics 11 (1), 28, 2020 | 27 | 2020 |
| Algorithm runtime prediction: The state of the art F Hutter, L Xu, HH Hoos, K Leyton-Brown CoRR, abs/1211.0906 11, 2012 | 25 | 2012 |
| Features for SAT L Xu, F Hutter, H Hoos, K Leyton-Brown University of British Columbia,, Tech. Rep, 2012 | 24 | 2012 |
| Remaining useful life prediction of rotating machinery using hierarchical deep neural network M Xia, T Li, L Liu, L Xu, S Gao, CW De Silva 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017 | 13 | 2017 |
| An efficient consistency algorithm for the temporal constraint satisfaction problem BY Choueiry, L Xu AI Communications 17 (4), 213-221, 2004 | 12 | 2004 |
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
