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04/28/2023
NNSplitter: An Active Defense Solution to DNN Model via Automated Weight Obfuscation
As a type of valuable intellectual property (IP), deep neural network (D...
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02/23/2023
MetaLDC: Meta Learning of Low-Dimensional Computing Classifiers for Fast On-Device Adaption
Fast model updates for unseen tasks on intelligent edge devices are cruc...
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12/03/2022
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints
Online optimization with multiple budget constraints is challenging sinc...
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10/16/2022
Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning
Continual learning faces a crucial challenge of catastrophic forgetting....
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08/17/2022
ObfuNAS: A Neural Architecture Search-based DNN Obfuscation Approach
Malicious architecture extraction has been emerging as a crucial concern...
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07/02/2022
Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity
By integrating domain knowledge with labeled samples, informed machine l...
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03/25/2022
A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural Accelerators
In view of the performance limitations of fully-decoupled designs for ne...
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03/18/2022
HDLock: Exploiting Privileged Encoding to Protect Hyperdimensional Computing Models against IP Stealing
Hyperdimensional Computing (HDC) is facing infringement issues due to st...
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03/18/2022
LeHDC: Learning-Based Hyperdimensional Computing Classifier
Thanks to the tiny storage and efficient execution, hyperdimensional Com...
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03/09/2022
A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices
By mimicking brain-like cognition and exploiting parallelism, hyperdimen...
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12/20/2021
Learning for Robust Combinatorial Optimization: Algorithm and Application
Learning to optimize (L2O) has recently emerged as a promising approach ...
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12/11/2021
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement
The rapid uptake of intelligent applications is pushing deep learning (D...
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11/01/2021
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
Convolutional neural networks (CNNs) are used in numerous real-world app...
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02/09/2021
Robust Bandit Learning with Imperfect Context
A standard assumption in contextual multi-arm bandit is that the true co...
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12/03/2020
Distributed Thompson Sampling
We study a cooperative multi-agent multi-armed bandits with M agents and...
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11/17/2020
A Quantitative Perspective on Values of Domain Knowledge for Machine Learning
With the exploding popularity of machine learning, domain knowledge in v...
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09/01/2020
Scaling Up Deep Neural Network Optimization for Edge Inference
Deep neural networks (DNNs) have been increasingly deployed on and integ...
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07/03/2020
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
Inference accuracy of deep neural networks (DNNs) is a crucial performan...
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06/16/2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets
To increase the trustworthiness of deep neural network (DNN) classifiers...
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06/10/2020
Adversarial Attacks on Brain-Inspired Hyperdimensional Computing-Based Classifiers
Being an emerging class of in-memory computing architecture, brain-inspi...
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02/29/2020
A Note on Latency Variability of Deep Neural Networks for Mobile Inference
Running deep neural network (DNN) inference on mobile devices, i.e., mob...
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01/18/2020
Your Noise, My Signal: Exploiting Switching Noise for Stealthy Data Exfiltration from Desktop Computers
Attacks based on power analysis have been long existing and studied, wit...
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10/07/2018