Furong Huang
Furong Huang
Assistant Professor of Computer Science, University of Maryland
Потвърден имейл адрес: umd.edu - Начална страница
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
Cold diffusion: Inverting arbitrary image transforms without noise
A Bansal, E Borgnia, HM Chu, JS Li, H Kazemi, F Huang, M Goldblum, ...
Thirty-seventh Conference on Neural Information Processing Systems, 2022
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
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
Online tensor methods for learning latent variable models
F Huang, UN Niranjan, MU Hakeem, A Anandkumar
The Journal of Machine Learning Research 16 (1), 2797-2835, 2015
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 (August), 2012
Learning mixtures of tree graphical models
A Anandkumar, DJ Hsu, F Huang, SM Kakade
Advances in Neural Information Processing Systems 25, 2012
On the possibilities of ai-generated text detection
S Chakraborty, AS Bedi, S Zhu, B An, D Manocha, F Huang
arXiv preprint arXiv:2304.04736, 2023
HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination & Visual Illusion in Large Vision-Language Models
TZ Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu ...
Understanding generalization through visualizations
WR Huang, Z Emam, M Goldblum, L Fowl, JK Terry, F Huang, T Goldstein
PMLR, 2020
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
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
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Y Sun, D Huo, F Huang
International Conference on Learning Representations, 2021
Convolutional dictionary learning through tensor factorization
F Huang, A Anandkumar
Feature Extraction: Modern Questions and Challenges, 116-129, 2015
Trustllm: Trustworthiness in large language models
L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ...
arXiv preprint arXiv:2401.05561, 2024
Label smoothing and logit squeezing: A replacement for adversarial training?
A Shafahi, A Ghiasi, F Huang, T Goldstein
arXiv preprint arXiv:1910.11585, 2019
AutoDAN: Automatic and interpretable adversarial attacks on large language models
S Zhu, R Zhang, B An, G Wu, J Barrow, Z Wang, F Huang, A Nenkova, ...
arXiv preprint arXiv:2310.15140, 2023
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
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