Furong Huang

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Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Sicheng ZhuUniversity of Maryland, College ParkVerified email at umd.edu
Micah GoldblumColumbia UniversityVerified email at columbia.edu
Bang AnUniversity of Maryland, College ParkVerified email at umd.edu
Yanchao SunApple, Inc.Verified email at umd.edu
Dinesh ManochaDistinguished University Professor, University of Maryland at College ParkVerified email at umd.edu
Amrit Singh BediAssistant Professor in Department of Computer Science, University of Central Florida, FL, USAVerified email at ucf.edu
Souradip ChakrabortyUniversity of Maryland, College Park | Past : ML Research@Walmart LabsVerified email at umd.edu
Ruijie ZhengUniversity of Maryland, College ParkVerified email at umd.edu
Mucong DingDepartment of Computer Science, University of MarylandVerified email at cs.umd.edu
Eitan BorgniaPhD Student UChicagoVerified email at uchicago.edu
Yongyuan LiangUniversity of Maryland, College ParkVerified email at umd.edu
Xiaoyu LiuPhD Student, University of Maryland, College ParkVerified email at umd.edu
Jonas GeipingELLIS Institute Tübingen & Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Xiyao WangPh.D. in University of Maryland, College ParkVerified email at umd.edu
Tahseen RabbaniPhD Student, University of MarylandVerified email at umd.edu
Yuancheng XuUniversity of Maryland, College ParkVerified email at umd.edu
Fuxiao LiuUniversity of Maryland, College ParkVerified email at umd.edu
Alec KoppelAI Research Lead, JP Morgan AI ResearchVerified email at jpmchase.com

Furong Huang

Associate Professor of Computer Science, University of Maryland

Verified email at umd.edu - Homepage

Trustworthy AI/ML Reinforcement Learning Generative AI


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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	1272	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	218	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	159*	2021
Position: TrustLLM: Trustworthiness in Large Language Models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... International Conference on Machine Learning, 20166-20270, 2024	157*	2024
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 ...	157*	2023
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	142	2020
Learning deep resnet blocks sequentially using boosting theory F Huang, J Ash, J Langford, R Schapire International Conference on Machine Learning, 2058-2067, 2018	131	2018
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	130	2012
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	108	2012
Position: On the Possibilities of AI-Generated Text Detection S Chakraborty, A Bedi, S Zhu, B An, D Manocha, F Huang Forty-first International Conference on Machine Learning, 2024	104*	2024
AutoDAN: interpretable gradient-based adversarial attacks on large language models S Zhu, R Zhang, B An, G Wu, J Barrow, Z Wang, F Huang, A Nenkova, ... First Conference on Language Modeling, 2023	104*	2023
Understanding generalization through visualizations WR Huang, Z Emam, M Goldblum, L Fowl, JK Terry, F Huang, T Goldstein PMLR, 2020	70	2020
Learning mixtures of tree graphical models A Anandkumar, DJ Hsu, F Huang, SM Kakade Advances in Neural Information Processing Systems 25, 2012	68*	2012
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	67	2022
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	66	2021
Fast detection of overlapping communities via online tensor methods F Huang, UN Niranjan, MU Hakeem, A Anandkumar arXiv preprint arXiv:1309.0787 40, 43, 2013	64*	2013
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Y Sun, D Huo, F Huang International Conference on Learning Representations, 2021	57*	2021
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	51	2010
VQ-GNN: A universal framework to scale up graph neural networks using vector quantization M Ding, K Kong, J Li, C Zhu, J Dickerson, F Huang, T Goldstein Advances in Neural Information Processing Systems 34, 6733-6746, 2021	49*	2021
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	47	2015

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