Carlos Guestrin

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Citations	81563	59036
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Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Tianqi ChenCarnegie Mellon UniversityVerified email at cmu.edu
Sameer SinghAssociate Professor, University of California IrvineVerified email at uci.edu
Marco Tulio RibeiroMicrosoft ResearchVerified email at cs.washington.edu
Joseph HellersteinJim Gray Professor of Computer Science, UC BerkeleyVerified email at berkeley.edu
Danny BicksonSr. Manager, AppleVerified email at cs.cmu.edu
Aapo KyrolaPh.D (Carnegie Mellon University, 2014)Verified email at cs.cmu.edu
Samuel MaddenMITVerified email at csail.mit.edu
Daphne KollerCEO and Founder, insitroVerified email at insitro.com
Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Christos FaloutsosCMUVerified email at cs.cmu.edu
Jeanne M. VanBriesenDepartment of Civil and Environmental Engineering at Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Mark PaskinGoogleVerified email at google.com
Ronald ParrProfessor of Computer Science, Duke UniversityVerified email at cs.duke.edu
Ben TaskarUniversity of WashingtonVerified email at cs.washington.edu
Dafna ShahafAssociate Professor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il
Emily B. FoxStanford UniversityVerified email at stanford.edu
Arvind KrishnamurthyShort-Dooley Professor, Univ. of WashingtonVerified email at cs.washington.edu
Luis CezeProfessor of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Jon KleinbergProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu

Carlos Guestrin

Professor, Stanford University

Verified email at stanford.edu - Homepage

Machine Learning Distributed Systems Artificial Intelligence Parallel Algorithms Sensor Networks


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Xgboost: A scalable tree boosting system T Chen, C Guestrin Proceedings of the 22nd acm sigkdd international conference on knowledge …, 2016	27365	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	12743	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	2848	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	2398	2012
Powergraph: Distributed graph-parallel computation on natural graphs JE Gonzalez, Y Low, H Gu, D Bickson, C Guestrin Presented as part of the 10th {USENIX} Symposium on Operating Systems Design …, 2012	2296	2012
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	1802	2008
Max-margin Markov networks B Taskar, C Guestrin, D Koller Advances in neural information processing systems 16, 2003	1732	2003
Anchors: High-precision model-agnostic explanations MT Ribeiro, S Singh, C Guestrin Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018	1645	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	1571	2004
Graphchi: Large-scale graph computation on just a {PC} A Kyrola, G Blelloch, C Guestrin Presented as part of the 10th {USENIX} Symposium on Operating Systems Design …, 2012	1395	2012
TVM: An automated end-to-end optimizing compiler for deep learning T Chen, T Moreau, Z Jiang, L Zheng, E Yan, M Cowan, H Shen, L Wang, ... arXiv preprint arXiv:1802.04799, 2018	1220	2018
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	1052	2014
Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining T Chen, C Guestrin	949	2016
Model-agnostic interpretability of machine learning MT Ribeiro, S Singh, C Guestrin arXiv preprint arXiv:1606.05386, 2016	851	2016
Stochastic gradient hamiltonian monte carlo T Chen, E Fox, C Guestrin International conference on machine learning, 1683-1691, 2014	832	2014
Beyond accuracy: Behavioral testing of NLP models with CheckList MT Ribeiro, T Wu, C Guestrin, S Singh arXiv preprint arXiv:2005.04118, 2020	676	2020
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	659	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	636	2008
Efficient solution algorithms for factored MDPs C Guestrin, D Koller, R Parr, S Venkataraman Journal of Artificial Intelligence Research 19, 399-468, 2003	632	2003
Training deep nets with sublinear memory cost T Chen, B Xu, C Zhang, C Guestrin arXiv preprint arXiv:1604.06174, 2016	620	2016

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