Yuan-Ting Hsieh – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-05-01T18:35:55Z http://www.open-lab.net/blog/feed/ Yuan-Ting Hsieh <![CDATA[Effortless Federated Learning on Mobile with NVIDIA FLARE and Meta ExecuTorch]]> http://www.open-lab.net/blog/?p=98560 2025-05-01T18:35:55Z 2025-04-11T18:37:54Z NVIDIA and the PyTorch team at Meta announced a groundbreaking collaboration that brings federated learning (FL) capabilities to mobile devices through the...]]>

NVIDIA and the PyTorch team at Meta announced a groundbreaking collaboration that brings federated learning (FL) capabilities to mobile devices through the integration of NVIDIA FLARE and ExecuTorch. NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that enables researchers and data scientists to adapt existing machine learning or deep learning workflows to a federated paradigm.

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Yuan-Ting Hsieh <![CDATA[Security for Data Privacy in Federated Learning with CUDA-Accelerated Homomorphic Encryption in XGBoost]]> http://www.open-lab.net/blog/?p=93870 2024-12-17T19:33:44Z 2024-12-18T21:30:00Z XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative...]]>

XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative training, NVIDIA has developed Federated XGBoost, an XGBoost plugin for federation learning. It covers vertical collaboration settings to jointly train XGBoost models across decentralized data sources, as well as horizontal histogram-based…

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Yuan-Ting Hsieh <![CDATA[Federated XGBoost Made Practical and Productive with NVIDIA FLARE]]> http://www.open-lab.net/blog/?p=82379 2024-07-25T18:19:23Z 2024-06-28T20:21:27Z XGBoost is a highly effective and scalable machine learning algorithm widely employed for regression, classification, and ranking tasks. Building on the...]]>

XGBoost is a highly effective and scalable machine learning algorithm widely employed for regression, classification, and ranking tasks. Building on the principles of gradient boosting, it combines the predictions of multiple weak learners, typically decision trees, to produce a robust overall model. XGBoost excels with large datasets and complex data structures, thanks to its efficient…

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Yuan-Ting Hsieh <![CDATA[Scalable Federated Learning with NVIDIA FLARE for Enhanced LLM Performance]]> http://www.open-lab.net/blog/?p=78348 2024-05-10T00:21:02Z 2024-02-29T21:00:00Z In the ever-evolving landscape of large language models (LLMs), effective data management is a key challenge. Data is at the heart of model performance. While...]]>

In the ever-evolving landscape of large language models (LLMs), effective data management is a key challenge. Data is at the heart of model performance. While most advanced machine learning algorithms are data-centric, necessary data can’t always be centralized. This is due to various factors such as privacy, regulation, geopolitics, copyright issues, and the sheer effort required to move vast…

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