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Learning Systems: Machine-Learning in Software Products and Learning-Based Analysis of Software Systems: Special Track at ISoLA 2016

LEVERAGING APPLICATIONS OF FORMAL METHODS, VERIFICATION AND VALIDATION, 2016, p.651-654

2016

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Learning Loss for Active Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.93-102

2019

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Automated Machine Learning: Methods, Systems, Challenges

1, 2019

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Machine Learning Control: Taming Nonlinear Dynamics and Turbulence

1, 2016

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Imbalanced Learning: Foundations, Algorithms, and Applications

1, 2013

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Meta-Transfer Learning for Few-Shot Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.403-412

2019

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Large Scale Incremental Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.374-382

2019

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Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

2019 IEEE Symposium on Security and Privacy (SP), 2019, p.739-753

2019

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Privacy-Preserving Deep Learning

Proceedings of the 22nd ACM SIGSAC Conference on computer and communications security, 2015, p.1310-1321

2015

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Learning Without Memorizing

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.5133-5141

2019

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Learning from Synthetic Humans

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.4627-4635

2017

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Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

2018 IEEE Symposium on Security and Privacy (SP), 2018, p.19-35

2018

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Task-Free Continual Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.11246-11255

2019

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Noise2Void - Learning Denoising From Single Noisy Images

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.2124-2132

2019

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Learning Non-maximum Suppression

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.6469-6477

2017

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Open Networked 'i-Learning': Models and Cases of 'Next-Gen' Learning

1. Aufl., 2010

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Task Agnostic Meta-Learning for Few-Shot Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.11711-11719

2019

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Parametric Contrastive Learning

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.695-704

2021

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Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.9042-9051

2021

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Learning a Deep Embedding Model for Zero-Shot Learning

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, p.3010-3019

2017

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Meta-Learning With Differentiable Convex Optimization

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.10649-10657

2019

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Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data

1, 2015

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Stealing Hyperparameters in Machine Learning

2018 IEEE Symposium on Security and Privacy (SP), 2018, p.36-52

2018

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Learning to Sample

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.2755-2764

2019

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Semi-Supervised Learning With Graph Learning-Convolutional Networks

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.11305-11312

2019

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Learning Systems: Machine-Learning in Software Products and Learning-Based Analysis of Software Systems: Special Track at ISoLA 2016

Learning Loss for Active Learning

Automated Machine Learning: Methods, Systems, Challenges

Machine Learning Control: Taming Nonlinear Dynamics and Turbulence

Imbalanced Learning: Foundations, Algorithms, and Applications

Meta-Transfer Learning for Few-Shot Learning

Large Scale Incremental Learning

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Privacy-Preserving Deep Learning

Learning Without Memorizing

Learning from Synthetic Humans

Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Task-Free Continual Learning

Noise2Void - Learning Denoising From Single Noisy Images

Learning Non-maximum Suppression

Open Networked 'i-Learning': Models and Cases of 'Next-Gen' Learning

Task Agnostic Meta-Learning for Few-Shot Learning

Parametric Contrastive Learning

Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

Learning a Deep Embedding Model for Zero-Shot Learning

Meta-Learning With Differentiable Convex Optimization

Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data

Stealing Hyperparameters in Machine Learning

Learning to Sample

Semi-Supervised Learning With Graph Learning-Convolutional Networks

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