Furong Huang

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	All	Since 2018
Citations	2705	2246
h-index	21	19
i10-index	32	30

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Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Yanchao SunUniversity of Maryland, College ParkVerified email at umd.edu
Micah GoldblumNew York UniversityVerified email at nyu.edu
Eitan BorgniaPhD Student UChicagoVerified email at uchicago.edu
Ruijie ZhengUniversity of Maryland, College ParkVerified email at umd.edu
Yongyuan LiangUniversity of Maryland, College ParkVerified email at mail2.sysu.edu.cn
Bang AnUniversity of MarylandVerified email at umd.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Yang YuanMassachusetts Institute of TechnologyVerified email at cs.cornell.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Zeyad EmamUniversity of MarylandVerified email at umd.edu
Niranjan Uma NareshVerified email at uci.edu
Arpit BansalUniversity of Maryland, College ParkVerified email at umd.edu
Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Vincent Y. F. TanProfessor, Department of Mathematics, National University of SingaporeVerified email at nus.edu.sg
Jonas GeipingResearch Group Leader ELLIS Institute & MPI-IS TübingenVerified email at tuebingen.mpg.de
Mucong DingDepartment of Computer Science, University of MarylandVerified email at cs.umd.edu
Amrit Singh BediResearch Scientist at University of Maryland, College Park, MD, USA.Verified email at umd.edu
Jingling LiUniversity of Maryland, College ParkVerified email at umd.edu

Furong Huang

Assistant Professor of Computer Science, University of Maryland

Verified email at umd.edu - Homepage

Trustworthy Machine Learning Reinforcement Learning Generative AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Escaping from saddle points—online stochastic gradient for tensor decomposition R Ge, F Huang, C Jin, Y Yuan Conference on learning theory, 797-842, 2015	1174	2015
High-dimensional structure estimation in Ising models: Local separation criterion A Anandkumar, VYF Tan, F Huang, AS Willsky The Annals of Statistics, 1346-1375, 2012	126	2012
Learning deep resnet blocks sequentially using boosting theory F Huang, J Ash, J Langford, R Schapire International Conference on Machine Learning, 2058-2067, 2018	115	2018
Online tensor methods for learning latent variable models F Huang, UN Niranjan, MU Hakeem, A Anandkumar Journal of Machine Learning Research 16, 2797-2835, 2015	109*	2015
Cold diffusion: Inverting arbitrary image transforms without noise A Bansal, E Borgnia, HM Chu, JS Li, H Kazemi, F Huang, M Goldblum, ... arXiv preprint arXiv:2208.09392, 2022	105	2022
High-dimensional Gaussian graphical model selection: Walk summability and local separation criterion A Anandkumar, VYF Tan, F Huang, AS Willsky Journal of Machine Learning Research 13, 2293-2337, 2012	101	2012
Convolutional Tensor-Train LSTM for Spatio-temporal Learning J Su, W Byeon, F Huang, J Kautz, A Anandkumar Advances in Neural Information Processing Systems, 2020	99	2020
Learning mixtures of tree graphical models A Anandkumar, DJ Hsu, F Huang, SM Kakade Advances in Neural Information Processing Systems 25, 2012	65*	2012
Understanding generalization through visualizations WR Huang, Z Emam, M Goldblum, L Fowl, JK Terry, F Huang, T Goldstein PMLR, 2020	58	2020
Prediction-based spectrum aggregation with hardware limitation in cognitive radio networks F Huang, W Wang, H Luo, G Yu, Z Zhang 2010 IEEE 71st Vehicular Technology Conference, 1-5, 2010	50	2010
Convolutional dictionary learning through tensor factorization F Huang, A Anandkumar Feature Extraction: Modern Questions and Challenges, 116-129, 2015	45	2015
Label smoothing and logit squeezing: A replacement for adversarial training? A Shafahi, A Ghiasi, F Huang, T Goldstein arXiv preprint arXiv:1910.11585, 2019	42	2019
Can you learn an algorithm? generalizing from easy to hard problems with recurrent networks A Schwarzschild, E Borgnia, A Gupta, F Huang, U Vishkin, M Goldblum, ... Advances in Neural Information Processing Systems 34, 6695-6706, 2021	39	2021
Who is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL Y Sun, R Zheng, Y Liang, F Huang The Tenth International Conference on Learning Representations, 2022	38	2022
Compact neural architecture designs by tensor representations J Su, J Li, X Liu, T Ranadive, C Coley, TC Tuan, F Huang Frontiers in artificial intelligence 5, 728761, 2022	34*	2022
Dp-instahide: Provably defusing poisoning and backdoor attacks with differentially private data augmentations E Borgnia, J Geiping, V Cherepanova, L Fowl, A Gupta, A Ghiasi, ... arXiv preprint arXiv:2103.02079, 2021	33	2021
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Y Sun, D Huo, F Huang International Conference on Learning Representations, 2021	33	2021
Understanding Generalization in Deep Learning via Tensor Methods J Li, Y Sun, J Su, T Suzuki, F Huang International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020	27*	2020
Sysml: The new frontier of machine learning systems A Ratner, D Alistarh, G Alonso, P Bailis, S Bird, N Carlini, B Catanzaro, ... arXiv preprint arXiv:1904.03257, 2019	26	2019
Guaranteed scalable learning of latent tree models F Huang, NU Naresh, I Perros, R Chen, J Sun, A Anandkumar Uncertainty in Artificial Intelligence, 883-893, 2020	25*	2020

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