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05/03/2023
New Adversarial Image Detection Based on Sentiment Analysis
Deep Neural Networks (DNNs) are vulnerable to adversarial examples, whil...
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03/11/2023
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey
Adversarial attacks and defenses in machine learning and deep neural net...
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12/13/2022
Privacy-preserving Security Inference Towards Cloud-Edge Collaborative Using Differential Privacy
Cloud-edge collaborative inference approach splits deep neural networks ...
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10/11/2022
On Uniform Confidence Intervals for the Tail Index and the Extreme Quantile
This paper presents two results concerning uniform confidence intervals ...
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09/30/2022
Double Graphs Regularized Multi-view Subspace Clustering
Recent years have witnessed a growing academic interest in multi-view su...
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09/28/2022
Global Weighted Tensor Nuclear Norm for Tensor Robust Principal Component Analysis
Tensor Robust Principal Component Analysis (TRPCA), which aims to recove...
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08/19/2022
Dispersed Pixel Perturbation-based Imperceptible Backdoor Trigger for Image Classifier Models
Typical deep neural network (DNN) backdoor attacks are based on triggers...
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03/09/2022
Error-based Knockoffs Inference for Controlled Feature Selection
Recently, the scheme of model-X knockoffs was proposed as a promising so...
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06/18/2021
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective
The vulnerability of deep neural networks to adversarial examples, which...
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04/20/2021
Semantic Segmentation by Improved Generative Adversarial Networks
While most existing segmentation methods usually combined the powerful f...
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03/15/2021
Shape-induced obstacle attraction and repulsion during dynamic locomotion
Robots still struggle to dynamically traverse complex 3-D terrain with m...
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03/03/2020
Data-Free Adversarial Perturbations for Practical Black-Box Attack
Neural networks are vulnerable to adversarial examples, which are malici...
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01/24/2020
6D Object Pose Regression via Supervised Learning on Point Clouds
This paper addresses the task of estimating the 6 degrees of freedom pos...
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10/07/2019
Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork
We propose a novel perspective to understand deep neural networks in an ...
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09/27/2019
Pruning from Scratch
Network pruning is an important research field aiming at reducing comput...
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01/08/2019
Efficient Minimum Distance Estimation of Pareto Exponent from Top Income Shares
We propose an efficient estimation method for the income Pareto exponent...
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12/14/2017
A Hierarchical Recurrent Neural Network for Symbolic Melody Generation
In recent years, neural networks have been used to generate music pieces...
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11/05/2017