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Brandon Bryant
A learner in Statistics, Machine Learning.
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【论文笔记12】Differential privacy based on importance weighting 基于重要性加权的差分隐私, Mach Learn 2013
目录导引系列传送Abstract系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variational Adversarial Active Learning, ICCV 2019【论文笔记04】Ranked原创 2021-04-24 19:44:03 · 338 阅读 · 0 评论 -
机器学习论文阅读笔记摘录，主动学习Active Learning，迁移学习Transfer Learning，差分隐私Differential Privacy，模型攻击Model Attack
笔记导引【Active Learning】【Transfer Learning】【Differential Privacy】【Model inversion attack】【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019 让网络自己学会预测这个数据的训练损失，从而在无标记Pool中找到valuable instances【论文笔记02】Active Learning For Convolutional Neura原创 2021-04-23 15:26:11 · 1935 阅读 · 2 评论 -
【论文笔记16】An Efficient Differential Privacy Logistic Classification Mechanism, 2019 IEEE IoT-J
原文链接AbstractIntroductionAlgorithm这里有一个非常简单基础的 ϵ-DP\epsilon \text{-DP}ϵ-DP 的证明Reference[1] Huang, Wen, et al. “An efficient differential privacy logistic classification mechanism.” IEEE Internet of Things Journal 6.6 (2019): 10620-10626....原创 2021-04-23 11:23:36 · 571 阅读 · 1 评论 -
【论文笔记15】Boosting and Differential Privacy, 对查询集进行boosting以达到对数据的差分隐私, IEEE ASFCS 2010
原文链接1 Abstract2 Introduction2.1 Summary of ResultsPrinciple Result: a technique for generating privacy-preserving synopses for any set of low-sensitivity queries (不限于计数查询). This is achieved by a novel use of boosting, together with the construction of原创 2021-04-19 22:00:03 · 629 阅读 · 1 评论 -
【论文笔记14】Transfer Learing via Minimizing the Performance Gap Between Domains, NIPS 2019
Reference原创 2021-04-19 21:53:15 · 237 阅读 · 0 评论 -
【论文笔记13】Differentially Private Optimal Transport: Application to Domain Adaptation, IJCAI 2019
目录导引系列传送AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variational Adversarial Active Learning, ICCV 2019【论文笔记0原创 2021-04-10 22:01:57 · 647 阅读 · 0 评论 -
【论文笔记11】 Deep Domain Adaptation With Differential Privay 差分隐私下的深度域泛化, IEEE TIFS 2020
目录导引系列传送AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variational Adversarial Active Learning, ICCV 2019【论文笔记0原创 2021-04-10 11:41:41 · 937 阅读 · 0 评论 -
【论文笔记10】A unified framework of ATL for cross-system recommendation 跨系统推荐的一种主动迁移学习框加, AI 2017
目录导引系列传送A unified framework of active transfer learning for cross-system recommendation1 AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set App原创 2021-04-03 14:21:54 · 520 阅读 · 0 评论 -
【论文笔记09】Differentially Private Hypothesis Transfer Learning 差分隐私迁移学习模型, ECML&PKDD 2018
目录导引系列传送Differentially Private Hypothesis Transfer Learning1 AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Vari原创 2021-04-03 13:10:37 · 821 阅读 · 1 评论 -
【论文笔记08】Model inversion attacks that exploit confidence information and basic countermeasures 模型反转攻击
目录导引系列传送Model inversion attacks that exploit confidence information and basic countermeasures1 Abstract2 Background2.1 ML basis2.2 ML APIs2.3 Threat models3 The Fredrikson et al. attack4 Map inverters for trees4.1 Decision Tree4.2 DT APIs5 Facial recogniti原创 2021-04-02 10:37:13 · 5447 阅读 · 0 评论 -
【论文笔记07】A Survey on Differentially Private Machine Learning 差分隐私机器学习综述, IEEE CIM 2020
目录导引系列传送A Survey on Differentially Private Machine LearningReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variational Ad原创 2021-03-31 09:21:56 · 1848 阅读 · 1 评论 -
【论文笔记06】Domain-Adversarial Training of Neural Networks, JMLR 2016
目录导引系列传送Domain-Adversarial Training of Neural Networks1 AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variation原创 2021-03-27 16:34:09 · 1752 阅读 · 1 评论 -
【论文笔记05】Active Transfer Learning, IEEE T CIRC SYST VID 2020
目录导引系列传送Active Transfer Learning1 AbstractReference系列传送【Active Learning】【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch, ICLR 2018【论文笔记03】Variational Adversarial Active原创 2021-03-27 16:28:22 · 803 阅读 · 2 评论 -
【论文笔记04】Ranked Batch-Mode Active Learning，ICCV 2016
目录导引系列传送VAAL1 Abstract2 Introduction3 Model3.13.23.3ExperimentsReference系列传送【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch，ICLR 2018【论文笔记03】VAAL原文传送《Variational Advers原创 2021-03-27 16:22:42 · 555 阅读 · 0 评论 -
【论文笔记03】Variational Adversarial Active Learning，ICCV 2019
目录导引系列传送VAAL1 Abstract2 Introduction3 Model3.13.23.3ExperimentsReference系列传送【论文笔记01】Learning Loss for Active Learning, CVPR 2019【论文笔记02】VAAL原文传送《Variational Adversarial Active Learning》1 Abstract2 Introduction3 Model3.13.23.3ExperimentsReferen原创 2021-03-27 16:18:04 · 926 阅读 · 0 评论 -
【论文笔记02】Active Learning For Convolutional Neural Networks: A Core-Set Approch，ICLR 2018
目录导引系列传送Core-SetAbstractContributeMethodExperimentsReference系列传送Core-SetAbstractContributeMethodExperimentsReference原创 2020-08-01 00:44:33 · 6083 阅读 · 8 评论 -
【论文笔记01】Learning Loss for Active Learning, CVPR 2019
目录导引写在前面Learning Loss for Active LearningAbstractContributionsMethodOverviewLoss Prediction ModuleLearning Loss插入链接与图片如何插入一段漂亮的代码片生成一个适合你的列表创建一个表格设定内容居中、居左、居右SmartyPants创建一个自定义列表如何创建一个注脚注释也是必不可少的KaTeX数学公式新的甘特图功能，丰富你的文章UML 图表FLowchart流程图导出与导入导出导入写在前面大家好，这原创 2020-07-24 20:24:53 · 2287 阅读 · 6 评论