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20162023
most citedCirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

177 citations · 449 across the 53 of their papers we have counts for

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Showing 2021Show all

13 papers · 1 filter

cs.LG2021

Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices

Sahidul Islam, Jieren Deng, Shanglin Zhou +3

Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with advances in deep neural networks (DNNs), have opened up new opportunities for enablin…

cs.CL2021★ 11 cited

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT

Bingbing Li, Hongwu Peng, Rajat Sainju +7

In this paper, we propose a novel gender bias detection method by utilizing attention map for transformer-based models. We 1) give an intuitive gender bias judgement method by comp…

cs.CL2021

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm

Shaoyi Huang, Dongkuan Xu, Ian E. H. Yen +8

Conventional wisdom in pruning Transformer-based language models is that pruning reduces the model expressiveness and thus is more likely to underfit rather than overfit. However,…

cs.IR2021

Dr. Top-k: Delegate-Centric Top-k on GPUs

Anil Gaihre, Da Zheng, Scott Weitze +5

Recent top- computation efforts explore the possibility of revising various sorting algorithms to answer top- queries on GPUs. These endeavors, unfortunately, perform signifi…

cs.AR2021★ 1 cited

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search

Hongwu Peng, Shiyang Chen, Zhepeng Wang +9

Molecular similarity search has been widely used in drug discovery to identify structurally similar compounds from large molecular databases rapidly. With the increasing size of ch…

quant-ph2021★ 8 cited

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs

Zhepeng Wang, Zhiding Liang, Shanglin Zhou +3

With the constant increase of the number of quantum bits (qubits) in the actual quantum computers, implementing and accelerating the prevalent deep learning on quantum computers ar…