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02/28/2023
Learning to Retain while Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation
Data-free Knowledge Distillation (DFKD) has gained popularity recently, ...
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06/17/2021
Class Balancing GAN with a Classifier in the Loop
Generative Adversarial Networks (GANs) have swiftly evolved to imitate i...
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01/15/2021
Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications
Pretrained deep models hold their learnt knowledge in the form of the mo...
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11/18/2020
Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation
Knowledge Distillation is an effective method to transfer the learning a...
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06/10/2020
Dataset Condensation with Gradient Matching
Efficient training of deep neural networks is an increasingly important ...
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04/27/2020
Adversarial Fooling Beyond "Flipping the Label"
Recent advancements in CNNs have shown remarkable achievements in variou...
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01/08/2020
iDLG: Improved Deep Leakage from Gradients
It is widely believed that sharing gradients will not leak private train...
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05/20/2019
Zero-Shot Knowledge Distillation in Deep Networks
Knowledge distillation deals with the problem of training a smaller mode...
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08/06/2018
Gray-box Adversarial Training
Adversarial samples are perturbed inputs crafted to mislead the machine ...
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08/03/2018
Ask, Acquire, and Attack: Data-free UAP Generation using Class Impressions
Deep learning models are susceptible to input specific noise, called adv...
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01/24/2018
Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations
Machine learning models are susceptible to adversarial perturbations: sm...
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12/09/2017
NAG: Network for Adversary Generation
Adversarial perturbations can pose a serious threat for deploying machin...
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08/22/2017
CNN Fixations: An unraveling approach to visualize the discriminative image regions
Deep convolutional neural networks (CNN) have revolutionized various fie...
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07/18/2017
Fast Feature Fool: A data independent approach to universal adversarial perturbations
State-of-the-art object recognition Convolutional Neural Networks (CNNs)...
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05/25/2017
Deep image representations using caption generators
Deep learning exploits large volumes of labeled data to learn powerful m...
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01/25/2016
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
Traditional architectures for solving computer vision problems and the d...
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04/24/2015
