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06/26/2023
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey
Deep learning-based intelligent vehicle perception has been developing p...
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12/21/2021
Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting
Deep neural networks (DNNs) have shown to provide superb performance in ...
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12/20/2021
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks
Deep neural networks (DNNs) have been proven to be effective in solving ...
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09/17/2020
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
Pretrained large-scale language models have increasingly demonstrated hi...
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04/24/2020
Computation on Sparse Neural Networks: an Inspiration for Future Hardware
Neural network models are widely used in solving many challenging proble...
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04/12/2020
A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods
To address the large model size and intensive computation requirement of...
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01/23/2020
BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
Accelerating DNN execution on various resource-limited computing platfor...
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01/20/2020
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
Weight pruning has been widely acknowledged as a straightforward and eff...
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08/29/2019
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM
The high computation and memory storage of large deep neural networks (D...
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06/09/2019
Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense
The worst-case training principle that minimizes the maximal adversarial...
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03/23/2019
Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM
Weight pruning and weight quantization are two important categories of D...
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12/31/2018
ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers
To facilitate efficient embedded and hardware implementations of deep ne...
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11/05/2018
A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM
Many model compression techniques of Deep Neural Networks (DNNs) have be...
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10/17/2018
Progressive Weight Pruning of Deep Neural Networks using ADMM
Deep neural networks (DNNs) although achieving human-level performance i...
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07/29/2018
ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs
Weight pruning methods of deep neural networks (DNNs) have been demonstr...
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04/10/2018
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
Weight pruning methods for deep neural networks (DNNs) have been investi...
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02/15/2018