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08/29/2023
OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams
How to get insights from relational data streams in a timely manner is a...
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07/05/2023
SoK: Privacy-Preserving Data Synthesis
As the prevalence of data analysis grows, safeguarding data privacy has ...
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08/13/2022
Practical Vertical Federated Learning with Unsupervised Representation Learning
As societal concerns on data privacy recently increase, we have witnesse...
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07/21/2022
UniFed: A Benchmark for Federated Learning Frameworks
Federated Learning (FL) has become a practical and popular paradigm in m...
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06/11/2021
Exploiting Record Similarity for Practical Vertical Federated Learning
As the privacy of machine learning has drawn increasing attention, feder...
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03/30/2021
Model-Contrastive Federated Learning
Federated learning enables multiple parties to collaboratively train a m...
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02/03/2021
Federated Learning on Non-IID Data Silos: An Experimental Study
Machine learning services have been emerging in many data-intensive appl...
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10/02/2020
Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer
Federated learning enables multiple parties to collaboratively learn a m...
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06/14/2020
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems
This paper presents and characterizes an Open Application Repository for...
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11/11/2019
Privacy-Preserving Gradient Boosting Decision Trees
The Gradient Boosting Decision Tree (GBDT) is a popular machine learning...
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11/11/2019
Practical Federated Gradient Boosting Decision Trees
Gradient Boosting Decision Trees (GBDTs) have become very successful in ...
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11/08/2019
Adaptive Kernel Value Caching for SVM Training
Support Vector Machines (SVMs) can solve structured multi-output learnin...
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07/23/2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Federated learning has been a hot research area in enabling the collabor...
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07/23/2019