Furong Huang
Furong Huang
Assistant Professor of Computer Science, University of Maryland
Verified email at - Homepage
Cited by
Cited by
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
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
Learning deep resnet blocks sequentially using boosting theory
F Huang, J Ash, J Langford, R Schapire
International Conference on Machine Learning, 2058-2067, 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
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
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
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
Learning mixtures of tree graphical models
A Anandkumar, DJ Hsu, F Huang, SM Kakade
Advances in Neural Information Processing Systems 25, 2012
Understanding generalization through visualizations
WR Huang, Z Emam, M Goldblum, L Fowl, JK Terry, F Huang, T Goldstein
PMLR, 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
Convolutional dictionary learning through tensor factorization
F Huang, A Anandkumar
Feature Extraction: Modern Questions and Challenges, 116-129, 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
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
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
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
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
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Y Sun, D Huo, F Huang
International Conference on Learning Representations, 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
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
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
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