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Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
To explore the vulnerability of deep neural networks (DNNs), many attack...
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JSRT: James-Stein Regression Tree
Regression tree (RT) has been widely used in machine learning and data m...
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DPAttack: Diffused Patch Attacks against Universal Object Detection
Recently, deep neural networks (DNNs) have been widely and successfully ...
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Improving Query Efficiency of Black-box Adversarial Attack
Deep neural networks (DNNs) have demonstrated excellent performance on v...
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Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning
Interpretability and effectiveness are two essential and indispensable r...
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Backdoor Learning: A Survey
Deep neural networks (DNNs) have demonstrated their power on many widely...
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Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters
Convolutional neural networks (CNNs) have been successfully used in a ra...
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Temporal Calibrated Regularization for Robust Noisy Label Learning
Deep neural networks (DNNs) exhibit great success on many tasks with the...
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Construction of MDS Euclidean Self-Dual Codes via Two Subsets
The parameters of a q-ary MDS Euclidean self-dual codes are completely d...
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Revisiting Loss Landscape for Adversarial Robustness
The study on improving the robustness of deep neural networks against ad...
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Matrix Smoothing: A Regularization for DNN with Transition Matrix under Noisy Labels
Training deep neural networks (DNNs) in the presence of noisy labels is ...
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Practical and Bilateral Privacy-preserving Federated Learning
Federated learning, as an emerging distributed training model of neural ...
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Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Skip connections are an essential component of current state-of-the-art ...
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Deep Flow Collaborative Network for Online Visual Tracking
The deep learning-based visual tracking algorithms such as MDNet achieve...
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Visual Privacy Protection via Mapping Distortion
Data privacy protection is an important research area, which is especial...
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Adversarial Defense Via Local Flatness Regularization
Adversarial defense is a popular and important research area. Due to its...
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Adaptive Regularization of Labels
Recently, a variety of regularization techniques have been widely applie...
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Learning Deep Hidden Nonlinear Dynamics from Aggregate Data
Learning nonlinear dynamics from diffusion data is a challenging problem...
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Dimensionality-Driven Learning with Noisy Labels
Datasets with significant proportions of noisy (incorrect) class labels ...
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Iterative Learning with Open-set Noisy Labels
Large-scale datasets possessing clean label annotations are crucial for ...
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Bayesian linear regression with Student-t assumptions
As an automatic method of determining model complexity using the trainin...
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Unifying Decision Trees Split Criteria Using Tsallis Entropy
The construction of efficient and effective decision trees remains a key...
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