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06/16/2021
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI
Recent research demonstrated the promise of using resistive random acces...
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04/16/2021
CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
Federated learning (FL) is an emerging distributed machine learning para...
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04/15/2021
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
Federated Learning (FL) is a novel distributed machine learning which al...
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11/19/2019
DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
The rapidly growing parameter volume of deep neural networks (DNNs) hind...
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07/22/2019
A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology
The Adiabatic Quantum-Flux-Parametron (AQFP) superconducting technology ...
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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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05/10/2018
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...
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03/28/2018
Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs
Both industry and academia have extensively investigated hardware accele...
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02/03/2018
An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing
With recent trend of wearable devices and Internet of Things (IoTs), it ...
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02/02/2018
VIBNN: Hardware Acceleration of Bayesian Neural Networks
Bayesian Neural Networks (BNNs) have been proposed to address the proble...
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10/10/2017
Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations
The recent breakthroughs of deep reinforcement learning (DRL) technique ...
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03/12/2017
Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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11/18/2016