Tom Goldstein

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	All	Since 2018
Citations	21446	16625
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i10-index	162	151

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Christoph StuderAssociate Professor at the Dept. of Information Technology and Electrical Engineering, ETH ZurichVerified email at ethz.ch
Zheng XuGoogle ResearchVerified email at google.com
Gavin TaylorUS Naval AcademyVerified email at usna.edu
S osherVerified email at math.ucla.edu
Ali ShafahiAppleVerified email at umd.edu
Richard BaraniukC. Sidney Burrus Professor, Electrical & Computer Engineering, Rice UniversityVerified email at rice.edu
W. Ronny HuangGoogle ResearchVerified email at google.com
Oscar CastañedaETH ZurichVerified email at ethz.ch
Giuseppe DurisiChalmers University of TechnologyVerified email at chalmers.se
Soham DeDeepMindVerified email at google.com
David A Bluemke, MD, PhDUniversity of Wisconsin- MadisonVerified email at wisc.edu
Xavier BressonAssoc Prof of Computer Science, National University of SingaporeVerified email at nus.edu.sg
Simon SetzerSaarland UniversityVerified email at mia.uni-saarland.de
Brendan O'DonoghueStanford University, DeepMindVerified email at alumni.stanford.edu
Wotao YinDAMO Academy, Alibaba Group USVerified email at alibaba-inc.com
Christopher SibleyAscendis Pharma N/AVerified email at ascendispharma.com
Kevin F. KellyIEEE Fellow, Electrical & Computer Engineering, Rice UniversityVerified email at rice.edu
Stephen BoydProfessor of Electrical Engineering, Computer Science, and Management Science, StanfordVerified email at stanford.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityVerified email at stanford.edu
Ioannis KoktzoglouNorthShore University HealthSystemVerified email at northshore.org

Tom Goldstein

Volpi-Cupal Professor of Computer Science, University of Maryland

Verified email at cs.umd.edu - Homepage

Numerical Optimization Machine Learning Distributed Computing Computer Vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The split Bregman method for L1-regularized problems T Goldstein, S Osher SIAM journal on imaging sciences 2 (2), 323-343, 2009	5075	2009
Visualizing the loss landscape of neural nets H Li, Z Xu, G Taylor, C Studer, T Goldstein Advances in neural information processing systems 31, 2018	1704	2018
Adversarial training for free! A Shafahi, M Najibi, MA Ghiasi, Z Xu, J Dickerson, C Studer, LS Davis, ... Advances in Neural Information Processing Systems 32, 2019	1163	2019
Poison frogs! targeted clean-label poisoning attacks on neural networks A Shafahi, WR Huang, M Najibi, O Suciu, C Studer, T Dumitras, ... Advances in neural information processing systems 31, 2018	946	2018
Fast alternating direction optimization methods T Goldstein, B O'Donoghue, S Setzer, R Baraniuk SIAM Journal on Imaging Sciences 7 (3), 1588-1623, 2014	857	2014
Geometric applications of the split Bregman method: segmentation and surface reconstruction T Goldstein, X Bresson, S Osher Journal of scientific computing 45, 272-293, 2010	586	2010
Freelb: Enhanced adversarial training for natural language understanding C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu arXiv preprint arXiv:1909.11764, 2019	391	2019
Quantized precoding for massive MU-MIMO S Jacobsson, G Durisi, M Coldrey, T Goldstein, C Studer IEEE Transactions on Communications 65 (11), 4670-4684, 2017	318	2017
Are adversarial examples inevitable? A Shafahi, WR Huang, C Studer, S Feizi, T Goldstein International Conference on Learning Representations, 2019	304	2019
Training neural networks without gradients: A scalable admm approach G Taylor, R Burmeister, Z Xu, B Singh, A Patel, T Goldstein International conference on machine learning, 2722-2731, 2016	292	2016
Convex phase retrieval without lifting via PhaseMax T Goldstein, C Studer International Conference on Machine Learning, 1273-1281, 2017	290*	2017
Dcan: Dual channel-wise alignment networks for unsupervised scene adaptation Z Wu, X Han, YL Lin, MG Uzunbas, T Goldstein, SN Lim, LS Davis Proceedings of the European Conference on Computer Vision (ECCV), 518-534, 2018	271	2018
Transferable clean-label poisoning attacks on deep neural nets C Zhu, WR Huang, H Li, G Taylor, C Studer, T Goldstein International Conference on Machine Learning, 7614-7623, 2019	270	2019
A field guide to forward-backward splitting with a FASTA implementation T Goldstein, C Studer, R Baraniuk arXiv preprint arXiv:1411.3406, 2014	251	2014
Splitting methods in communication, imaging, science, and engineering R Glowinski, SJ Osher, W Yin Springer, 2017	244	2017
Certified data removal from machine learning models C Guo, T Goldstein, A Hannun, L Van Der Maaten arXiv preprint arXiv:1911.03030, 2019	218	2019
Training quantized nets: A deeper understanding H Li, S De, Z Xu, C Studer, H Samet, T Goldstein Advances in Neural Information Processing Systems 30, 2017	213	2017
Making an invisibility cloak: Real world adversarial attacks on object detectors Z Wu, SN Lim, LS Davis, T Goldstein Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020	207	2020
Universal adversarial training A Shafahi, M Najibi, Z Xu, J Dickerson, LS Davis, T Goldstein Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5636-5643, 2020	182	2020
A watermark for large language models J Kirchenbauer, J Geiping, Y Wen, J Katz, I Miers, T Goldstein arXiv preprint arXiv:2301.10226, 2023	158	2023

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