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08/22/2023
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks
Graph Convolutional Networks (GCNs) are pivotal in extracting latent inf...
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08/20/2023
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference
The growth of the Machine-Learning-As-A-Service (MLaaS) market has highl...
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04/24/2023
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration
Biologically inspired Spiking Neural Networks (SNNs) have attracted sign...
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02/05/2023
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference
The proliferation of deep learning (DL) has led to the emergence of priv...
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11/30/2022
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off
Over-parameterization of deep neural networks (DNNs) has shown high pred...
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11/06/2022
Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach
Traffic state prediction in a transportation network is paramount for ef...
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09/20/2022
PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference
The rapid growth and deployment of deep learning (DL) has witnessed emer...
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09/11/2022
Towards Sparsification of Graph Neural Networks
As real-world graphs expand in size, larger GNN models with billions of ...
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08/07/2022
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
Transformers are considered one of the most important deep learning mode...
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06/21/2022
An Automatic and Efficient BERT Pruning for Edge AI Systems
With the yearning for deep learning democratization, there are increasin...
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10/19/2021
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization
State-of-the-art Transformer-based models, with gigantic parameters, are...
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10/15/2021
