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07/20/2023
PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks
Collaborative inference has been a promising solution to enable resource...
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07/10/2023
Fed-CPrompt: Contrastive Prompt for Rehearsal-Free Federated Continual Learning
Federated continual learning (FCL) learns incremental tasks over time fr...
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12/05/2022
FedTiny: Pruned Federated Learning Towards Specialized Tiny Models
Neural network pruning has been a well-established compression technique...
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07/21/2022
Federated Semi-Supervised Domain Adaptation via Knowledge Transfer
Given the rapidly changing machine learning environments and expensive d...
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07/21/2022
Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning
Despite the success of AI-enabled onboard perception, on-ramp merging ha...
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04/22/2022
Pay "Attention" to Adverse Weather: Weather-aware Attention-based Object Detection
Despite the recent advances of deep neural networks, object detection fo...
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02/07/2022
Membership Inference Attacks and Defenses in Neural Network Pruning
Neural network pruning has been an essential technique to reduce the com...
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09/08/2021
FedZKT: Zero-Shot Knowledge Transfer towards Heterogeneous On-Device Models in Federated Learning
Federated learning enables distributed devices to collaboratively learn ...
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06/18/2021
A Vertical Federated Learning Framework for Horizontally Partitioned Labels
Vertical federated learning is a collaborative machine learning framewor...
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09/21/2020
ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles
Deep neural networks (DNNs) have become the essential components for var...
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08/31/2020
Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks
Recently web applications have been widely used in enterprises to assist...
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12/08/2018
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks
Utilizing recently introduced concepts from statistics and quantitative ...
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07/09/2018
Adaptive Adversarial Attack on Scene Text Recognition
Recent studies have shown that state-of-the-art deep learning models are...
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02/07/2018
Leveraging Uncertainty for Effective Malware Mitigation
A promising avenue for improving the effectiveness of behavioral-based m...
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12/19/2017
Adversarial Examples: Attacks and Defenses for Deep Learning
With rapid progress and great successes in a wide spectrum of applicatio...
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12/04/2017
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection
In this paper, we introduce and evaluate PROPEDEUTICA, a novel methodolo...
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09/28/2017