We stand with Ukraine

We stand with Ukraine

Qizhou Wang

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

Known people with the same name:

Qizhou Wang 001 (University of Melbourne, School of Computing and Information Systems, Melbourne, Australia)

Bibliography

2026

HIDFlowNet: A flow-based deep network for hyperspectral image denoising.

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Inf. Fusion, 2026

2025

W-DOE: Wasserstein Distribution-Agnostic Outlier Exposure.

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IEEE Trans. Pattern Anal. Mach. Intell., May, 2025

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning.

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CoRR, May, 2025

GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models.

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CoRR, March, 2025

Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond.

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Kilian Q. Weinberger

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Towards Effective Evaluations and Comparisons for LLM Unlearning Methods.

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Masashi Sugiyama

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Scheduling optimization of underground mine trackless transportation based on improved estimation of distribution algorithm.

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Expert Syst. Appl., 2024

Combination prediction of underground mine rock drilling time based on seasonal and trend decomposition using Loess.

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Eng. Appl. Artif. Intell., 2024

Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning.

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Masashi Sugiyama

CoRR, 2024

Do CLIPs Always Generalize Better than ImageNet Models?

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CoRR, 2024

A Sober Look at the Robustness of CLIPs to Spurious Features.

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Temporal-Contextual Event Learning for Pedestrian Crossing Intent Prediction.

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Mingsheng Shang

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Proceedings of the Neural Information Processing - 31st International Conference, 2024

2023

Underground mine truck travel time prediction based on stacking integrated learning.

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Eng. Appl. Artif. Intell., April, 2023

Are All Unseen Data Out-of-Distribution?

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CoRR, 2023

Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s.

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[DOI]

Maksim Makarenko

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Arturo Burguete-Lopez

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Silvio Giancola

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Andrea Fratalocchi

CoRR, 2023

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Augment Distributions for Out-of-distribution Detection.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Out-of-distribution Detection with Implicit Outlier Transformation.

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Marcus Kalander

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation.

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IEEE Trans. Pattern Anal. Mach. Intell., 2022

Towards Lightweight Black-Box Attacks against Deep Neural Networks.

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CoRR, 2022

Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images.

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Comput. Electron. Agric., 2022

Watermarking for Out-of-distribution Detection.

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Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Lightweight Black-Box Attack Against Deep Neural Networks.

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Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders.

[BibT_eX]

[DOI]

Maksim Makarenko

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Arturo Burguete-Lopez

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Silvio Giancola

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Andrea Fratalocchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

SDA-GAN: Unsupervised Image Translation Using Spectral Domain Attention-Guided Generative Adversarial Network.

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[DOI]

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Maksim Makarenko

CoRR, 2021

Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks.

[BibT_eX]

[DOI]

Maksim Makarenko

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Arturo Burguete-Lopez

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Andrea Fratalocchi

Adv. Intell. Syst., 2021

Probabilistic Margins for Instance Reweighting in Adversarial Training.

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Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fraud Detection under Multi-Sourced Extremely Noisy Annotations.

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Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Learning with Group Noise.

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Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model.

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Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

A game method for improving the interpretability of convolution neural network.

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CoRR, 2019

2018

How to improve the interpretability of kernel learning.

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CoRR, 2018

How far from automatically interpreting deep learning.

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CoRR, 2018

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