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08/21/2023
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer
Deep neural networks are vulnerable to adversarial examples crafted by a...
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06/08/2023
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Transfer-based attack adopts the adversarial examples generated on the s...
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10/27/2021
Constrained Optimization Involving Nonconvex â„“_p Norms: Optimality Conditions, Algorithm and Convergence
This paper investigates the optimality conditions for characterizing the...
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06/23/2021
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning
Federated Learning (FL) has become an active and promising distributed m...
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06/22/2021
Learned Interpretable Residual Extragradient ISTA for Sparse Coding
Recently, the study on learned iterative shrinkage thresholding algorith...
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06/18/2021
Quantized Neural Networks via -1, +1 Encoding Decomposition and Acceleration
The training of deep neural networks (DNNs) always requires intensive re...
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03/22/2021
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling
Video super-resolution (VSR) aims at restoring a video in low-resolution...
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10/31/2020
Differentially Private ADMM Algorithms for Machine Learning
In this paper, we study efficient differentially private alternating dir...
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10/21/2020
Boosting Gradient for White-Box Adversarial Attacks
Deep neural networks (DNNs) are playing key roles in various artificial ...
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08/24/2020
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution
Spherical videos, also known as 360 (panorama) videos, can be viewed wit...
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07/25/2020
Video Super Resolution Based on Deep Learning: A comprehensive survey
In recent years, deep learning has made great progress in the fields of ...
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12/02/2019
Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization
Large-scale non-convex sparsity-constrained problems have recently gaine...
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11/10/2019
A unified approach for projections onto the intersection of â„“_1 and â„“_2 balls or spheres
This paper focuses on designing a unified approach for computing the pro...
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07/21/2019
signADAM: Learning Confidences for Deep Neural Networks
In this paper, we propose a new first-order gradient-based algorithm to ...
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07/17/2019
CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation
This paper proposes a novel cascaded U-Net for brain tumor segmentation....
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07/01/2015
