Golovin, Daniel

14 publications

AutoML 2022 Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song, Sagi Perel, Chansoo Lee, Greg Kochanski, Daniel Golovin

ICLR 2020 Gradientless Descent: High-Dimensional Zeroth-Order Optimization Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi Zhang

ICML 2020 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization Richard Zhang, Daniel Golovin

NeurIPS 2015 Hidden Technical Debt in Machine Learning Systems D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison

ICML 2013 Large-Scale Learning with Less RAM via Randomization Daniel Golovin, D. Sculley, Brendan McMahan, Michael Young

JAIR 2011 Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization Daniel Golovin, Andreas Krause

AAAI 2011 Dynamic Resource Allocation in Conservation Planning Daniel Golovin, Andreas Krause, Beth Gardner, Sarah J. Converse, Steve Morey

IJCAI 2011 Randomized Sensing in Adversarial Environments Andreas Krause, Alex Roper, Daniel Golovin

COLT 2010 Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization Daniel Golovin, Andreas Krause

NeurIPS 2010 Near-Optimal Bayesian Active Learning with Noisy Observations Daniel Golovin, Andreas Krause, Debajyoti Ray

NeurIPS 2009 Online Learning of Assignments Matthew Streeter, Daniel Golovin, Andreas Krause

NeurIPS 2008 An Online Algorithm for Maximizing Submodular Functions Matthew Streeter, Daniel Golovin

AAAI 2007 Combining Multiple Heuristics Online Matthew J. Streeter, Daniel Golovin, Stephen F. Smith

AAAI 2007 Restart Schedules for Ensembles of Problem Instances Matthew J. Streeter, Daniel Golovin, Stephen F. Smith