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08/06/2023
StyleEDL: Style-Guided High-order Attention Network for Image Emotion Distribution Learning
Emotion distribution learning has gained increasing attention with the t...
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07/29/2023
An Automata-Theoretic Approach to Synthesizing Binarized Neural Networks
Deep neural networks, (DNNs, a.k.a. NNs), have been widely used in vario...
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06/27/2023
Verifying Safety of Neural Networks from Topological Perspectives
Neural networks (NNs) are increasingly applied in safety-critical system...
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05/05/2023
Repairing Deep Neural Networks Based on Behavior Imitation
The increasing use of deep neural networks (DNNs) in safety-critical sys...
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12/01/2022
AI Empowered Net-RCA for 6G
6G is envisioned to offer higher data rate, improved reliability, ubiqui...
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10/28/2022
Scalable Spectral Clustering with Group Fairness Constraints
There are synergies of research interests and industrial efforts in mode...
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10/09/2022
Safety Verification for Neural Networks Based on Set-boundary Analysis
Neural networks (NNs) are increasingly applied in safety-critical system...
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02/17/2021
DepOwl: Detecting Dependency Bugs to Prevent Compatibility Failures
Applications depend on libraries to avoid reinventing the wheel. Librari...
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02/10/2021
On the Properties of Kullback-Leibler Divergence Between Gaussians
Kullback-Leibler (KL) divergence is one of the most important divergence...
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10/24/2020
Keyphrase Extraction with Dynamic Graph Convolutional Networks and Diversified Inference
Keyphrase extraction (KE) aims to summarize a set of phrases that accura...
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08/17/2020
AP-Loss for Accurate One-Stage Object Detection
One-stage object detectors are trained by optimizing classification-loss...
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02/09/2020
Input Validation for Neural Networks via Runtime Local Robustness Verification
Local robustness verification can verify that a neural network is robust...
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02/09/2020
Out-of-Distribution Detection with Distance Guarantee in Deep Generative Models
Recent research has shown that it is challenging to detect out-of-distri...
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10/17/2019
Not Just Cloud Privacy: Protecting Client Privacy in Teacher-Student Learning
Ensuring the privacy of sensitive data used to train modern machine lear...
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09/06/2019
SEdroid: A Robust Android Malware Detector using Selective Ensemble Learning
For the dramatic increase of Android malware and low efficiency of manua...
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06/05/2019
Private Deep Learning with Teacher Ensembles
Privacy-preserving deep learning is crucial for deploying deep neural ne...
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04/12/2019
Towards Accurate One-Stage Object Detection with AP-Loss
One-stage object detectors are trained by optimizing classification-loss...
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02/25/2019
Pretraining-Based Natural Language Generation for Text Summarization
In this paper, we propose a novel pretraining-based encoder-decoder fram...
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12/26/2018
Adversarial Attack and Defense on Graph Data: A Survey
Deep neural networks (DNNs) have been widely applied in various applicat...
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12/04/2018
Dynamic Sounding for Multi-User MIMO in Wireless LANs
Consumer electronic (CE) devices increasingly rely on wireless local are...
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11/17/2018
Boosting the Robustness Verification of DNN by Identifying the Achilles's Heel
Deep Neural Network (DNN) is a widely used deep learning technique. How ...
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11/13/2018
Private Model Compression via Knowledge Distillation
The soaring demand for intelligent mobile applications calls for deployi...
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09/11/2018
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction
With the development of cloud computing and big data, the reliability of...
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09/10/2018
Deep Learning Towards Mobile Applications
Recent years have witnessed an explosive growth of mobile devices. Mobil...
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09/10/2018
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud
The increasing demand for on-device deep learning services calls for a h...
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03/16/2018
Combining Symbolic Execution and Model Checking to Verify MPI Programs
Message Passing Interface (MPI) is the standard paradigm of programming ...
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08/22/2017
Scheduling Constraint Based Abstraction Refinement for Multi-Threaded Program Verification
Bounded model checking is among the most efficient techniques for the au...
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08/17/2017
