Daniel Golovin

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Andreas KrauseProfessor of Computer Science, ETH ZurichPatvirtintas el. paštas inf.ethz.ch
Benjamin SolnikGooglePatvirtintas el. paštas google.com
Subhodeep MoitraGooglePatvirtintas el. paštas google.com
Todd PhillipsGoogle AdsPatvirtintas el. paštas google.com
Matthew StreeterGoogle, Inc.Patvirtintas el. paštas mattstreeter.org
H. Brendan McMahanResearch Scientist, Google SeattlePatvirtintas el. paštas google.com
Debajyoti RayCaltechPatvirtintas el. paštas caltech.edu
Stephen F. SmithResearch Professor of Robotics, Carnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Guy BlellochProfessor of Computer Science, Carnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Adam WiermanCarl F Braun Professor of Computing+Mathematical Sciences, CaltechPatvirtintas el. paštas caltech.edu
Federico EcheniquePatvirtintas el. paštas caltech.edu
Sarah J ConverseUSGS, Washington Cooperative Fish and Wildlife Research Unit, University of WashingtonPatvirtintas el. paštas uw.edu
Vineet GoyalColumbia UniversityPatvirtintas el. paštas ieor.columbia.edu
R RaviCarnegie Mellon UnviersityPatvirtintas el. paštas andrew.cmu.edu
Bruce MaggsProfessor of Computer Science, Duke UniversityPatvirtintas el. paštas cs.duke.edu
Viswanath NagarajanUniversity of MichiganPatvirtintas el. paštas umich.edu
Mohit SinghProfessor, Georgia Institute of TechnologyPatvirtintas el. paštas gatech.edu
Beth GardnerAssociate Professor of Wildlife Biology, University of WashingtonPatvirtintas el. paštas uw.edu
Kanat TangwongsanMahidol University International CollegePatvirtintas el. paštas mahidol.edu
Charlie GarrodCarnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu

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Daniel Golovin

Google

Patvirtintas el. paštas google.com - Pagrindinis puslapis

Machine Learning Algorithms Computational Economics


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Hidden technical debt in machine learning systems D Sculley, G Holt, D Golovin, E Davydov, T Phillips, D Ebner, ... Advances in neural information processing systems 28, 2015	1694	2015
Ad click prediction: a view from the trenches HB McMahan, G Holt, D Sculley, M Young, D Ebner, J Grady, L Nie, ... Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	1161	2013
Submodular function maximization. A Krause, D Golovin Tractability 3 (71-104), 3, 2014	1130	2014
Google vizier: A service for black-box optimization D Golovin, B Solnik, S Moitra, G Kochanski, J Karro, D Sculley Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017	929	2017
Adaptive submodularity: Theory and applications in active learning and stochastic optimization D Golovin, A Krause Journal of Artificial Intelligence Research 42, 427-486, 2011	836	2011
Machine learning: The high interest credit card of technical debt D Sculley, G Holt, D Golovin, E Davydov, T Phillips, D Ebner, ... SE4ML: software engineering for machine learning (NIPS 2014 Workshop) 8, 2014	380	2014
An online algorithm for maximizing submodular functions M Streeter, D Golovin Advances in Neural Information Processing Systems 21, 2008	318	2008
Near-optimal bayesian active learning with noisy observations D Golovin, A Krause, D Ray Advances in Neural Information Processing Systems 23, 2010	247	2010
Combining multiple heuristics online M Streeter, D Golovin, SF Smith AAAI, 1197-1203, 2007	112	2007
Online distributed sensor selection D Golovin, M Faulkner, A Krause Proceedings of the 9th ACM/IEEE International Conference on Information …, 2010	94	2010
Max-min fair allocation of indivisible goods D Golovin School of Computer Science, Carnegie Mellon University, 2005	91	2005
Online learning of assignments M Streeter, D Golovin, A Krause Advances in neural information processing systems 22, 2009	87	2009
Random hypervolume scalarizations for provable multi-objective black box optimization R Zhang, D Golovin International conference on machine learning, 11096-11105, 2020	82	2020
Gradientless descent: High-dimensional zeroth-order optimization D Golovin, J Karro, G Kochanski, C Lee, X Song, Q Zhang arXiv preprint arXiv:1911.06317, 2019	77	2019
Approximating the k-multicut problem D Golovin, V Nagarajan, M Singh SODA 6, 621-630, 2006	59	2006
Strongly history-independent hashing with applications GE Blelloch, D Golovin 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), 272-282, 2007	56	2007
Online submodular maximization under a matroid constraint with application to learning assignments D Golovin, A Krause, M Streeter arXiv preprint arXiv:1407.1082, 2014	54	2014
Dynamic resource allocation in conservation planning D Golovin, A Krause, B Gardner, S Converse, S Morey Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 1331-1336, 2011	41	2011
A revealed preference approach to computational complexity in economics F Echenique, D Golovin, A Wierman Proceedings of the 12th ACM conference on Electronic commerce, 101-110, 2011	38	2011
All-norms and all-l_p-norms approximation algorithms D Golovin, A Gupta, A Kumar, K Tangwongsan IARCS Annual Conference on Foundations of Software Technology and …, 2008	35	2008

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