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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Challenges and Beneficiations of differential privacy in transfer learning and federated learning
迁移学习 联邦学习 差分隐私
2023/4/13
Differential privacy is one of the most common techniques in privacy-preserving machine learning due to its rigorous math definition and theoretical results. Transfer learning and Federated learning a...
EXTRACTION OF BUILT-UP AREAS USING CONVOLUTIONAL NEURAL NETWORKS AND TRANSFER LEARNING FROM SENTINEL-2 SATELLITE IMAGES
Built-up Area Extraction Convolutional Neural Networks Deep Learning Sentinel-2 Images Transfer Learning
2018/5/11
With rapid globalization, the extent of built-up areas is continuously increasing. Extraction of features for classifying built-up areas that are more robust and abstract is a leading research topic f...
TRANSFER LEARNING BASED ON LOGISTIC REGRESSION
Transfer Learning Domain Adaptation Logistic Regression Machine Learning Knowledge Transfer Remote Sensing
2015/9/21
In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for tra...
A Geometric Framework for Transfer Learning Using Manifold Alignment
Dimensionality Reduction Manifold Alignment Multiscale Analysis Representation Learning Topic Model Transfer Learning
2014/12/18
Many machine learning problems involve dealing with a large amount of high-dimensional data across diverse domains. In addition, annotating or labeling the data is expensive as it involves significant...
Transfer Learning for Constituency-Based Grammars。
Sparse coding for multitask and transfer learning
Sparse coding multitask transfer learning
2012/11/23
We present an extension of sparse coding to the problems of multitask and transfer learning. The central assumption of the method is that the tasks parameters are well approximated by sparse linear co...
Improving accuracy and power with transfer learning using a meta-analytic database
Meta-analysis,fMRI,multiple comparison,machine learning
2012/11/23
Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on an...