Xgboost: A scalable tree boosting system T Chen, C Guestrin Proceedings of the 22nd acm sigkdd international conference on knowledge …, 2016 | 40277 | 2016 |
" Why should i trust you?" Explaining the predictions of any classifier MT Ribeiro, S Singh, C Guestrin Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 17923 | 2016 |
Cost-effective outbreak detection in networks J Leskovec, A Krause, C Guestrin, C Faloutsos, J VanBriesen, N Glance Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 3097 | 2007 |
Distributed graphlab: A framework for machine learning in the cloud Y Low, J Gonzalez, A Kyrola, D Bickson, C Guestrin, JM Hellerstein arXiv preprint arXiv:1204.6078, 2012 | 2484 | 2012 |
{PowerGraph}: Distributed {Graph-Parallel} computation on natural graphs JE Gonzalez, Y Low, H Gu, D Bickson, C Guestrin 10th USENIX symposium on operating systems design and implementation (OSDI …, 2012 | 2457 | 2012 |
Anchors: High-precision model-agnostic explanations MT Ribeiro, S Singh, C Guestrin Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 2280 | 2018 |
Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies. A Krause, A Singh, C Guestrin Journal of Machine Learning Research 9 (2), 2008 | 1964 | 2008 |
Max-margin Markov networks B Taskar, C Guestrin, D Koller Advances in neural information processing systems 16, 2003 | 1801 | 2003 |
{TVM}: An automated {End-to-End} optimizing compiler for deep learning T Chen, T Moreau, Z Jiang, L Zheng, E Yan, H Shen, M Cowan, L Wang, ... 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 1713 | 2018 |
Model-driven data acquisition in sensor networks A Deshpande, C Guestrin, SR Madden, JM Hellerstein, W Hong Proceedings of the Thirtieth international conference on Very large data …, 2004 | 1605 | 2004 |
Stanford alpaca: An instruction-following llama model R Taori, I Gulrajani, T Zhang, Y Dubois, X Li, C Guestrin, P Liang, ... | 1546 | 2023 |
{GraphChi}:{Large-Scale} graph computation on just a {PC} A Kyrola, G Blelloch, C Guestrin 10th USENIX symposium on operating systems design and implementation (OSDI …, 2012 | 1474 | 2012 |
Model-agnostic interpretability of machine learning MT Ribeiro, S Singh, C Guestrin arXiv preprint arXiv:1606.05386, 2016 | 1150 | 2016 |
Graphlab: A new framework for parallel machine learning Y Low, JE Gonzalez, A Kyrola, D Bickson, CE Guestrin, J Hellerstein arXiv preprint arXiv:1408.2041, 2014 | 1103 | 2014 |
Stochastic gradient hamiltonian monte carlo T Chen, E Fox, C Guestrin International conference on machine learning, 1683-1691, 2014 | 1033 | 2014 |
Beyond accuracy: Behavioral testing of NLP models with CheckList MT Ribeiro, T Wu, C Guestrin, S Singh arXiv preprint arXiv:2005.04118, 2020 | 994 | 2020 |
Training deep nets with sublinear memory cost T Chen, B Xu, C Zhang, C Guestrin arXiv preprint arXiv:1604.06174, 2016 | 897 | 2016 |
Efficient solution algorithms for factored MDPs C Guestrin, D Koller, R Parr, S Venkataraman Journal of Artificial Intelligence Research 19, 399-468, 2003 | 677 | 2003 |
Learning structured prediction models: A large margin approach B Taskar, V Chatalbashev, D Koller, C Guestrin Proceedings of the 22nd international conference on Machine learning, 896-903, 2005 | 674 | 2005 |
The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms A Ostfeld, JG Uber, E Salomons, JW Berry, WE Hart, CA Phillips, ... Journal of water resources planning and management 134 (6), 556-568, 2008 | 673 | 2008 |