Furong Huang

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Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Tom GoldsteinVolpi-Cupal Associate Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Micah GoldblumNew York UniversityVerified email at nyu.edu
Yanchao SunUniversity of Maryland, College ParkVerified email at umd.edu
Eitan BorgniaPhD Student UChicagoVerified email at uchicago.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
Niranjan Uma NareshVerified email at uci.edu
Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Vincent Y. F. TanDean's Chair Associate Professor, National University of SingaporeVerified email at nus.edu.sg
Zeyad EmamUniversity of MarylandVerified email at umd.edu
Ruijie ZhengUniversity of Maryland, College ParkVerified email at umd.edu
Jingling LiUniversity of Maryland, College ParkVerified email at umd.edu
Arpit BansalUniversity of Maryland, College ParkVerified email at umd.edu
Mucong DingDepartment of Computer Science, University of MarylandVerified email at cs.umd.edu
Amin GhiasiGraduate Research Assistant, University of MarylandVerified email at umd.edu
Arjun GuptaPerception Engineer at ZiplineVerified email at flyzipline.com
Jonas GeipingPostdoc at University of Maryland, College ParkVerified email at umd.edu
Chen ZhuGoogle DeepmindVerified email at google.com

Furong Huang

Assistant Professor of Computer Science, University of Maryland

Verified email at umd.edu - Homepage

Machine Learning Reinforcement Learning Deep Learning and Theory Non-convex Optimization Spectral Methods


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	1103	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	121	2012
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	106*	2015
Learning deep resnet blocks sequentially using boosting theory F Huang, J Ash, J Langford, R Schapire International Conference on Machine Learning, 2058-2067, 2018	101	2018
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	81	2020
Learning mixtures of tree graphical models A Anandkumar, DJ Hsu, F Huang, SM Kakade Advances in Neural Information Processing Systems 25, 2012	61*	2012
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	53	2022
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
Understanding generalization through visualizations WR Huang, Z Emam, M Goldblum, L Fowl, JK Terry, F Huang, T Goldstein PMLR, 2020	47	2020
Convolutional dictionary learning through tensor factorization F Huang, A Anandkumar Feature extraction: modern questions and challenges, 116-129, 2015	42	2015
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, 2022	32*	2022
Label smoothing and logit squeezing: A replacement for adversarial training? A Shafahi, A Ghiasi, F Huang, T Goldstein arXiv preprint arXiv:1910.11585, 2019	31	2019
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Y Sun, D Huo, F Huang International Conference on Learning Representations, 2021	26	2021
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
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	25	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	24	2022
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	24*	2020
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	23	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	23*	2020

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