Hongxin Wei

Orcid: 0000-0002-8973-2843

According to our database1, Hongxin Wei authored at least 44 papers between 2014 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Multiple-instance Learning from Triplet Comparison Bags.
ACM Trans. Knowl. Discov. Data, May, 2024

On the Noise Robustness of In-Context Learning for Text Generation.
CoRR, 2024

G-ACIL: Analytic Learning for Exemplar-Free Generalized Class Incremental Learning.
CoRR, 2024

Learning with Noisy Foundation Models.
CoRR, 2024

TorchCP: A Library for Conformal Prediction based on PyTorch.
CoRR, 2024

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss.
CoRR, 2024

Exploring Learning Complexity for Downstream Data Pruning.
CoRR, 2024

Open-Vocabulary Calibration for Vision-Language Models.
CoRR, 2024

Does Confidence Calibration Help Conformal Prediction?
CoRR, 2024

2023
Deep Learning From Multiple Noisy Annotators as A Union.
IEEE Trans. Neural Networks Learn. Syst., December, 2023

Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., December, 2023

Multiple-Instance Learning From Unlabeled Bags With Pairwise Similarity.
IEEE Trans. Knowl. Data Eng., November, 2023

Natural robustness of machine learning in the open world
PhD thesis, 2023

Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition.
CoRR, 2023

Conformal Prediction for Deep Classifier via Label Ranking.
CoRR, 2023

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks.
CoRR, 2023

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection.
CoRR, 2023

CroSel: Cross Selection of Confident Pseudo Labels for Partial-Label Learning.
CoRR, 2023

On the Importance of Feature Separability in Predicting Out-Of-Distribution Error.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Regression with Cost-based Rejection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mitigating Memorization of Noisy Labels by Clipping the Model Prediction.
Proceedings of the International Conference on Machine Learning, 2023

A Generalized Unbiased Risk Estimator for Learning with Augmented Classes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Logit Clipping for Robust Learning against Label Noise.
CoRR, 2022

ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Can Adversarial Training Be Manipulated By Non-Robust Features?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Mitigating Neural Network Overconfidence with Logit Normalization.
Proceedings of the International Conference on Machine Learning, 2022

Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets.
Proceedings of the International Conference on Machine Learning, 2022

α-MF Detection Based on Spatial Correlation of Sea Clutter.
Proceedings of the 22nd IEEE International Conference on Communication Technology, 2022

GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Embedding-Augmented Generalized Matrix Factorization for Recommendation With Implicit Feedback.
IEEE Intell. Syst., 2021

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multiple-Instance Learning from Similar and Dissimilar Bags.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Creating Efficient Blockchains for the Internet of Things by Coordinated Satellite-Terrestrial Networks.
IEEE Wirel. Commun., 2020

Rethinking Blockchains in the Internet of Things Era from a Wireless Communication Perspective.
IEEE Netw., 2020

MetaInfoNet: Learning Task-Guided Information for Sample Reweighting.
CoRR, 2020

5G Embraces Satellites for 6G Ubiquitous IoT: Basic Models for Integrated Satellite Terrestrial Networks.
CoRR, 2020

Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2018
Queue-aware energy-efficient scheduling and power allocation with feedback reduction in small-cell networks.
Sci. China Inf. Sci., 2018

2016
Queue-aware energy-efficient scheduling and power allocation in small-cell networks with interference.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2016

2014
Feedback Reduction for Queue-aware Coordinated Multi-user Scheduling in Small-cell Networks.
Proceedings of the 2014 IEEE Military Communications Conference, 2014

Queue-aware energy-efficient scheduling in small-cell networks.
Proceedings of the IEEE International Conference on Communications, 2014


  Loading...