Jerry Yao-Chieh Hu

According to our database¹, Jerry Yao-Chieh Hu authored at least 23 papers between 2023 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

AlignAb: Pareto-Optimal Energy Alignment for Designing Nature-Like Antibodies.

[BibT_eX]

[DOI]

CoRR, 2024

On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality.

[BibT_eX]

[DOI]

CoRR, 2024

Transformers are Deep Optimizers: Provable In-Context Learning for Deep Model Training.

[BibT_eX]

[DOI]

CoRR, 2024

Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency.

[BibT_eX]

[DOI]

CoRR, 2024

On Differentially Private String Distances.

[BibT_eX]

[DOI]

CoRR, 2024

Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes.

[BibT_eX]

[DOI]

Jerry Yao-Chieh Hu

Dennis Wu

Han Liu

CoRR, 2024

Differentially Private Kernel Density Estimation.

[BibT_eX]

[DOI]

CoRR, 2024

On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs).

[BibT_eX]

[DOI]

CoRR, 2024

Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models.

[BibT_eX]

[DOI]

CoRR, 2024

Decoupled Alignment for Robust Plug-and-Play Adaptation.

[BibT_eX]

[DOI]

CoRR, 2024

Enhancing Jailbreak Attack Against Large Language Models through Silent Tokens.

[BibT_eX]

[DOI]

CoRR, 2024

Nonparametric Modern Hopfield Models.

[BibT_eX]

[DOI]

CoRR, 2024

Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.

[BibT_eX]

[DOI]

CoRR, 2024

BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Outlier-Efficient Hopfield Layers for Large Transformer-Based Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e.

[BibT_eX]

[DOI]

CoRR, 2023

Feature Programming for Multivariate Time Series Prediction.

[BibT_eX]

[DOI]

CoRR, 2023

On Sparse Modern Hopfield Model.

[BibT_eX]

[DOI]

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

Feature Programming for Multivariate Time Series Prediction.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Jerry Yao-Chieh Hu

Timeline

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Bibliography

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