Carlos Guestrin

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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 SinghUniversity of California, IrvineVerified email at uci.edu
Joseph HellersteinJim Gray Professor of Computer Science, UC BerkeleyVerified email at berkeley.edu
Danny BicksonSr. Manager, AppleVerified email at cs.cmu.edu
Marco Tulio RibeiroMicrosoft ResearchVerified email at cs.washington.edu
Aapo KyrolaPh.D (Carnegie Mellon University, 2014)Verified email at cs.cmu.edu
Daphne KollerCEO and Founder, insitroVerified email at insitro.com
Samuel MaddenMITVerified email at csail.mit.edu
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
Amol DeshpandeProfessorVerified email at cs.umd.edu
Mark PaskinGoogleVerified email at google.com
Ronald ParrProfessor of Computer Science, Duke UniversityVerified email at cs.duke.edu
Anupam GuptaProfessor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Dafna ShahafAssistant Professor of Computer Science, The Hebrew University of JerusalemVerified email at cs.huji.ac.il
Ajit Paul SinghSenior Staff Software Engineer, UberVerified email at alumni.cmu.edu
Jon KleinbergProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Ben TaskarUniversity of WashingtonVerified email at cs.washington.edu

Carlos Guestrin

Amazon Professor of Machine Learning, University of Washington

Verified email at cs.washington.edu - Homepage

Machine Learning Distributed Systems Artificial Intelligence Parallel Algorithms Sensor Networks


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Xgboost: A scalable tree boosting system T Chen, C Guestrin Proceedings of the 22nd acm sigkdd international conference on knowledge …, 2016	10605	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	5370	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	2415	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	2105	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 …, 2012	1877	2012
Max-margin Markov networks BTCGD Koller Advances in neural information processing systems 16, 25, 2004	1742	2004
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	1502	2004
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	1470	2008
Graphchi: Large-scale graph computation on just a {PC} A Kyrola, G Blelloch, C Guestrin 10th {USENIX} Symposium on Operating Systems Design and Implementation …, 2012	1148	2012
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	914	2014
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	633	2005
Anchors: High-precision model-agnostic explanations MT Ribeiro, S Singh, C Guestrin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	631	2018
Distributed regression: an efficient framework for modeling sensor network data C Guestrin, P Bodik, R Thibaux, M Paskin, S Madden Proceedings of the 3rd international symposium on Information processing in …, 2004	565	2004
Efficient solution algorithms for factored MDPs C Guestrin, D Koller, R Parr, S Venkataraman Journal of Artificial Intelligence Research 19, 399-468, 2003	564	2003
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	541	2008
Near-optimal sensor placements: Maximizing information while minimizing communication cost A Krause, C Guestrin, A Gupta, J Kleinberg Proceedings of the 5th international conference on Information processing in …, 2006	540	2006
Multiagent Planning with Factored MDPs. C Guestrin, D Koller, R Parr NIPS 1, 1523-1530, 2001	523	2001
Stochastic gradient hamiltonian monte carlo T Chen, E Fox, C Guestrin International conference on machine learning, 1683-1691, 2014	505	2014
Near-optimal sensor placements in gaussian processes C Guestrin, A Krause, AP Singh Proceedings of the 22nd international conference on Machine learning, 265-272, 2005	500	2005
Near-optimal nonmyopic value of information in graphical models A Krause, CE Guestrin arXiv preprint arXiv:1207.1394, 2012	472	2012

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