Ao Ren | DeepAI

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Yu Zhang
406 publications
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123 publications
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118 publications
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75 publications
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68 publications
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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...

0 Geng Yuan, et al. ∙

∙ 04/16/2021

CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework

Federated learning (FL) is an emerging distributed machine learning para...

0 Yu Zhang, et al. ∙

∙ 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...

0 Li Li, et al. ∙

∙ 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...

0 Ao Ren, et al. ∙

∙ 07/22/2019

A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology

The Adiabatic Quantum-Flux-Parametron (AQFP) superconducting technology ...

0 Ruizhe Cai, et al. ∙

∙ 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...

10 Ao Ren, et al. ∙

∙ 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...

0 Zhe Li, et al. ∙

∙ 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...

0 Caiwen Ding, et al. ∙

∙ 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 ...

0 Xiaolong Ma, et al. ∙

∙ 02/02/2018

VIBNN: Hardware Acceleration of Bayesian Neural Networks

Bayesian Neural Networks (BNNs) have been proposed to address the proble...

0 Ruizhe Cai, et al. ∙

∙ 10/10/2017

Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations

The recent breakthroughs of deep reinforcement learning (DRL) technique ...

0 Hongjia Li, et al. ∙

∙ 03/12/2017

Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks

Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...

0 Ji Li, et al. ∙

∙ 11/18/2016

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

With recent advancing of Internet of Things (IoTs), it becomes very attr...

0 Ao Ren, et al. ∙

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