Articles with public access mandates - Sharon LiLearn more
Not available anywhere: 1
PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning
H Wang, R Xiao, Y Li, L Feng, G Niu, G Chen, J Zhao
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Mandates: US National Science Foundation, US Department of Defense, National Natural …
Available somewhere: 25
Stacked Generative Adversarial Networks
X Huang, Y Li, O Poursaeed, J Hopcroft, S Belongie
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Mandates: US Department of Defense
Out-of-Distribution Detection with Deep Nearest Neighbors
Y Sun, Y Ming, X Zhu, Y Li
In Proceedings of International Conference on Machine Learning (ICML), 2022
Mandates: US National Science Foundation, US Department of Defense
Mitigating Neural Network Overconfidence with Logit Normalization
H Wei, R Xie, H Cheng, L Feng, B An, Y Li
In Proceedings of International Conference on Machine Learning (ICML), 2022
Mandates: National Natural Science Foundation of China
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
J Yang, P Wang, D Zou, Z Zhou, K Ding, W Peng, H Wang, G Chen, B Li, ...
NeurIPS Datasets and Benchmarks Track, 2022
Mandates: National Research Foundation, Singapore
Uncovering the small community structure in large networks: A local spectral approach
Y Li, K He, D Bindel, JE Hopcroft
Proceedings of the 24th international conference on world wide web, 658-668, 2015
Mandates: National Natural Science Foundation of China
PiCO: Contrastive Label Disambiguation for Partial Label Learning
H Wang, R Xiao, S Li, L Feng, G Niu, G Chen, J Zhao
International Conference on Learning Representations (ICLR), 2022
Mandates: National Natural Science Foundation of China
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
J Chen, Y Li, X Wu, Y Liang, S Jha
Proceedings of European Conference on Machine Learning and Principles and …, 2021
Mandates: US National Science Foundation, US Department of Defense
Local spectral clustering for overlapping community detection
Y Li, K He, K Kloster, D Bindel, J Hopcroft
ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (2), 1-27, 2018
Mandates: US Department of Defense, National Natural Science Foundation of China
Is Out-of-Distribution Detection Learnable?
Z Fang, Y Li, J Lu, J Dong, B Han, F Liu
Advances in Neural Information Processing Systems (NeurIPS), 2022
Mandates: US Department of Defense, Australian Research Council, National Natural …
The Lifecycle and Cascade of Social Messaging Groups
J Qiu, Y Li, J Tang, Z Lu, H Ye, B Chen, Q Yang, JE Hopcroft
Proceedings of the 25th International Conference on World Wide Web, 311-320, 2016
Mandates: National Natural Science Foundation of China
Detecting overlapping communities from local spectral subspaces
K He, Y Sun, D Bindel, J Hopcroft, Y Li
2015 IEEE international conference on data mining, 769-774, 2015
Mandates: National Natural Science Foundation of China
Understanding the Loss Surface of Neural Networks for Binary Classification
S Liang, R Sun, Y Li, R Srikant
International Conference on Machine Learning (ICML), 2835-2843, 2018
Mandates: US National Science Foundation
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
M Cai, H Zhang, H Huang, Q Geng, Y Li, G Huang
Proceedings of International Conference on Computer Vision (ICCV), 2021, 2021
Mandates: National Natural Science Foundation of China
SIREN: Shaping Representations for Detecting Out-of-Distribution Objects
X Du, G Gozum, Y Ming, Y Li
Advances in Neural Information Processing Systems, 2022
Mandates: US Department of Defense
Towards Measuring and Inferring User Interest From Gaze
Y Li, P Xu, D Lagun, V Navalpakkam
Proceedings of 26th International Conference on World Wide Web (WWW), 2017
Mandates: US Department of Defense
SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning
H Wang, M Xia, Y Li, Y Mao, L Feng, G Chen, J Zhao
Advances in Neural Information Processing Systems (NeurIPS), 2022
Mandates: National Natural Science Foundation of China
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
H Wei, H Zhuang, R Xie, L Feng, G Niu, B An, Y Li
In Proceedings of International Conference on Machine Learning (ICML), 2023
Mandates: US Department of Defense, National Natural Science Foundation of China …
Dream the impossible: Outlier imagination with diffusion models
X Du, Y Sun, X Zhu, Y Li
Advances in Neural Information Processing Systems (NeurIPS), 2023
Mandates: US National Science Foundation, US Department of Defense
How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?
Y Ming, Y Li
International Journal of Computer Vision (IJCV), 2023
Mandates: US National Science Foundation, US Department of Defense
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