Kaiwen Zhou

Affiliations:

Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong

According to our database¹, Kaiwen Zhou authored at least 34 papers between 2018 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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On csauthors.net:

Bibliography

2025

MESH - Understanding Videos Like Human: Measuring Hallucinations in Large Video Models.

[BibT_eX]

[DOI]

CoRR, September, 2025

2024

Efficient private SCO for heavy-tailed data via averaged clipping.

[BibT_eX]

[DOI]

Mach. Learn., December, 2024

Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration.

[BibT_eX]

[DOI]

CoRR, 2024

HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection.

[BibT_eX]

[DOI]

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

RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models.

[BibT_eX]

[DOI]

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

Enhancing Neural Subset Selection: Integrating Background Information into Set Representations.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Evolving Domain Generalization through Dynamic Latent Representations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes.

[BibT_eX]

[DOI]

CoRR, 2023

Towards Understanding Feature Learning in Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

CoRR, 2023

Understanding and Improving Feature Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

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

Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

[BibT_eX]

[DOI]

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

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Novel Extrapolation Technique to Accelerate WMMSE.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Efficient Private SCO for Heavy-Tailed Data via Clipping.

[BibT_eX]

[DOI]

CoRR, 2022

Pareto Invariant Risk Minimization.

[BibT_eX]

[DOI]

CoRR, 2022

An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms.

[BibT_eX]

[DOI]

CoRR, 2022

On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions.

[BibT_eX]

[DOI]

Lai Tian

Kaiwen Zhou

Anthony Man-Cho So

Proceedings of the International Conference on Machine Learning, 2022

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization.

[BibT_eX]

[DOI]

Kaiwen Zhou

Anthony Man-Cho So

James Cheng

CoRR, 2021

Local Reweighting for Adversarial Training.

[BibT_eX]

[DOI]

CoRR, 2021

2020

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2020

Edit Distance Embedding using Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Convolutional Embedding for Edit Distance.

[BibT_eX]

[DOI]

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates.

[BibT_eX]

[DOI]

Kaiwen Zhou

Anthony Man-Cho So

James Cheng

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tight Convergence Rate of Gradient Descent for Eigenvalue Computation.

[BibT_eX]

[DOI]

Qinghua Ding

Kaiwen Zhou

James Cheng

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Direct Acceleration of SAGA using Sampled Negative Momentum.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Norm-Range Partition: A Univiseral Catalyst for LSH based Maximum Inner Product Search (MIPS).

[BibT_eX]

[DOI]

CoRR, 2018

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2018

A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates.

[BibT_eX]

[DOI]

Kaiwen Zhou

Fanhua Shang

James Cheng

Proceedings of the 35th International Conference on Machine Learning, 2018

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

ASVRG: Accelerated Proximal SVRG.

[BibT_eX]

[DOI]

Proceedings of The 10th Asian Conference on Machine Learning, 2018

Kaiwen Zhou

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