Kezhi Kong

Cituota

	Visi	Nuo 2019
Šaltiniai	659	658
h-rodyklė	9	9
i10-rodyklė	9	9

240

120

180

2019202020212022202320244 6 52 159 203 234

Viešas pasiekiamumas

Peržiūrėti viską

8 straipsniai

0 straipsnių

pasiekiami

nepasiekiami

Pagal finansavimo įpareigojimus

Bendraautoriai

Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandPatvirtintas el. paštas cs.umd.edu
Mucong DingDepartment of Computer Science, University of MarylandPatvirtintas el. paštas cs.umd.edu
Chen ZhuMetaPatvirtintas el. paštas meta.com
Renkun NiCapital One, AI FoundationPatvirtintas el. paštas cs.umd.edu
John KirchenbauerUniversity of Maryland, College ParkPatvirtintas el. paštas umd.edu
Micah GoldblumColumbia UniversityPatvirtintas el. paštas columbia.edu
Guohao LiUniversity of Oxford, CAMEL-AI.orgPatvirtintas el. paštas robots.ox.ac.uk
Bernard GhanemProfessor, King Abdullah University of Science and TechnologyPatvirtintas el. paštas kaust.edu.sa
Furong HuangAssociate Professor of Computer Science, University of MarylandPatvirtintas el. paštas umd.edu
Zheng XuGoogle ResearchPatvirtintas el. paštas google.com
Hao-Zhe FengState Key Lab of CAD&CG, Zhejiang UniversityPatvirtintas el. paštas zju.edu.cn
W. Ronny HuangGoogle ResearchPatvirtintas el. paštas google.com
Wei ChenState Key Lab of CAD&CG, Zhejiang universityPatvirtintas el. paštas cad.zju.edu.cn
John P. DickersonAssociate Professor of Computer Science, University of Maryland & Chief Scientist, Arthur AIPatvirtintas el. paštas cs.umd.edu
Jingling LiUniversity of Maryland, College ParkPatvirtintas el. paštas umd.edu
Yuxin MaSouthern University of Science and TechnologyPatvirtintas el. paštas sustech.edu.cn

Stebėti

Kezhi Kong

University of Maryland, College Park

Patvirtintas el. paštas cs.umd.edu - Pagrindinis puslapis

Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Robust optimization as data augmentation for large-scale graphs K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	215*	2022
On the Reliability of Watermarks for Large Language Models J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah, K Kong, ... arXiv preprint arXiv:2306.04634, 2023	110	2023
Data augmentation for meta-learning R Ni, M Goldblum, A Sharaf, K Kong, T Goldstein International Conference on Machine Learning, 8152-8161, 2021	91	2021
Gradinit: Learning to initialize neural networks for stable and efficient training C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein Advances in Neural Information Processing Systems 34, 16410-16422, 2021	68	2021
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	48*	2021
A closer look at distribution shifts and out-of-distribution generalization on graphs M Ding, K Kong, J Chen, J Kirchenbauer, M Goldblum, D Wipf, F Huang, ...	36*	2021
GOAT: A Global Transformer on Large-scale Graphs K Kong, J Chen, J Kirchenbauer, R Ni, CB Bruss, T Goldstein International Conference on Machine Learning 2023, 2023	33	2023
Shot-vae: semi-supervised deep generative models with label-aware elbo approximations HZ Feng, K Kong, M Chen, T Zhang, M Zhu, W Chen Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7413-7421, 2021	31*	2021
Exploring linear projections for revealing clusters, outliers, and trends in subsets of multi-dimensional datasets J Xia, L Gao, K Kong, Y Zhao, Y Chen, X Kui, Y Liang Journal of Visual Languages & Computing 48, 52-60, 2018	12	2018
Insta-rs: Instance-wise randomized smoothing for improved robustness and accuracy C Chen, K Kong, P Yu, J Luque, T Goldstein, F Huang arXiv preprint arXiv:2103.04436, 2021	7*	2021
OpenTab: Advancing large language models as open-domain table reasoners K Kong, J Zhang, Z Shen, B Srinivasan, C Lei, C Faloutsos, H Rangwala, ... arXiv preprint arXiv:2402.14361, 2024	6	2024
A Visual Analytics Approach for Traffic Flow Prediction Ensembles. K Kong, Y Ma, C Ye, J Lu, X Chen, W Zhang, W Chen PG (Short Papers and Posters), 61-64, 2018	2	2018
Towards Generalized and Scalable Machine Learning on Structured Data K Kong University of Maryland, College Park, 2024		2024
Visualization of neo-epidermis formation and evaluation of wound closure using UV fluorescence excitation imaging at two wavelengths (Conference Presentation) Y Wang, W Cai, K Kong, X Jia, RR Anderson, W Franco Photonics in Dermatology and Plastic Surgery 2019 10851, 108510H, 2019		2019

Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.

Straipsniai 1–14

Šaltinių per metus

Dubliuoti šaltiniai

Sujungti šaltiniai

Pridėti bendraautoriusBendraautoriai

Stebėti

Cituota

Bendraautoriai