Improving the improved training of wasserstein gans: A consistency term and its dual effect X Wei, B Gong, Z Liu, W Lu, L Wang International Conference on Learning Representations (ICLR), 2018 | 325 | 2018 |
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective MA Jamal, M Brown, MH Yang, L Wang, B Gong IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 320 | 2020 |
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks Y Li, L Li, L Wang, T Zhang, B Gong International Conference on Machine Learning (ICML), 2019 | 296 | 2019 |
Aet vs. aed: Unsupervised representation learning by auto-encoding transformations rather than data L Zhang, GJ Qi, L Wang, J Luo IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 256 | 2019 |
Detecting Anomaly in Big Data System Logs Using Convolutional Neural Network S Lu, X Wei, Y Li, L Wang IEEE Cyber Science and Technology Congress (CyberSciTech), 151-158, 2018 | 226 | 2018 |
Runtime analysis of atomicity for multithreaded programs L Wang, SD Stoller IEEE Transactions on Software Engineering 32 (2), 93-110, 2006 | 220 | 2006 |
Depthwise Convolution is All You Need for Learning Multiple Visual Domains Y Guo, Y Li, R Feris, L Wang, T Rosing AAAI Conference on Artificial Intelligence (AAAI), 2019 | 172 | 2019 |
Accurate and efficient runtime detection of atomicity errors in concurrent programs L Wang, SD Stoller Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice …, 2006 | 138 | 2006 |
A semi-supervised two-stage approach to learning from noisy labels Y Ding, L Wang, D Fan, B Gong 2018 IEEE Winter conference on applications of computer vision (WACV), 1215-1224, 2018 | 127 | 2018 |
Data replication in data intensive scientific applications with performance guarantee D Nukarapu, B Tang, L Wang, S Lu IEEE Transactions on Parallel and Distributed Systems 22 (8), 1299-1306, 2010 | 123 | 2010 |
Automated type-based analysis of data races and atomicity A Sasturkar, R Agarwal, L Wang, SD Stoller Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of …, 2005 | 122 | 2005 |
Detecting potential deadlocks with static analysis and run-time monitoring R Agarwal, L Wang, SD Stoller Haifa Verification Conference, 191-207, 2005 | 117 | 2005 |
P&P: A combined push-pull model for resource monitoring in cloud computing environment H Huang, L Wang 2010 IEEE 3rd International Conference on Cloud Computing, 260-267, 2010 | 106 | 2010 |
A performance modeling and optimization analysis tool for sparse matrix-vector multiplication on GPUs P Guo, L Wang, P Chen IEEE Transactions on Parallel and Distributed Systems 25 (5), 1112-1123, 2014 | 105 | 2014 |
The united states covid-19 forecast hub dataset EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ... Scientific data 9 (1), 462, 2022 | 101 | 2022 |
Log-based abnormal task detection and root cause analysis for spark S Lu, BB Rao, X Wei, B Tak, L Wang, L Wang 2017 IEEE International Conference on Web Services (ICWS), 389-396, 2017 | 101 | 2017 |
Static analysis of atomicity for programs with non-blocking synchronization L Wang, SD Stoller Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of …, 2005 | 94 | 2005 |
Optimized run-time race detection and atomicity checking using partial discovered types R Agarwal, A Sasturkar, L Wang, SD Stoller Proceedings of the 20th IEEE/ACM International Conference on Automated …, 2005 | 92 | 2005 |
MRGIS: A MapReduce-Enabled high performance workflow system for GIS Q Chen, L Wang, Z Shang 2008 IEEE Fourth International Conference on eScience, 646-651, 2008 | 88 | 2008 |
Convolutional neural networks with refined loss functions for the real-time crash risk analysis R Yu, Y Wang, Z Zou, L Wang Transportation research part C: emerging technologies 119, 102740, 2020 | 86 | 2020 |