Nicholas D. Lane

research

∙ 07/25/2023

Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation

The unprecedented accuracy of convolutional neural networks (CNNs) acros...

0 Stylianos I. Venieris, et al. ∙

research

∙ 07/19/2023

TinyTrain: Deep Neural Network Training at the Extreme Edge

On-device training is essential for user personalisation and privacy. Wi...

0 Young D. Kwon, et al. ∙

research

∙ 07/14/2023

L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning

The ubiquity of camera-enabled devices has led to large amounts of unlab...

0 Yasar Abbas Ur Rehman, et al. ∙

research

∙ 07/12/2023

FDAPT: Federated Domain-adaptive Pre-training for Language Models

Combining Domain-adaptive Pre-training (DAPT) with Federated Learning (F...

0 Lekang Jiang, et al. ∙

research

∙ 06/06/2023

FedVal: Different good or different bad in federated learning

Federated learning (FL) systems are susceptible to attacks from maliciou...

0 Viktor Valadi, et al. ∙

research

∙ 05/26/2023

vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer

Most work in privacy-preserving federated learning (FL) has been focusin...

0 Xinchi Qiu, et al. ∙

research

∙ 05/25/2023

Are We There Yet? Product Quantization and its Hardware Acceleration

Conventional multiply-accumulate (MAC) operations have long dominated co...

0 Javier Fernandez-Marques, et al. ∙

research

∙ 05/20/2023

Privacy in Multimodal Federated Human Activity Recognition

Human Activity Recognition (HAR) training data is often privacy-sensitiv...

0 Alex Iacob, et al. ∙

research

∙ 05/18/2023

Efficient Vertical Federated Learning with Secure Aggregation

The majority of work in privacy-preserving federated learning (FL) has b...

4 Xinchi Qiu, et al. ∙

research

∙ 05/04/2023

Can Fair Federated Learning reduce the need for Personalisation?

Federated Learning (FL) enables training ML models on edge clients witho...

0 Alex Iacob, et al. ∙

research

∙ 04/15/2023

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates

The privacy-sensitive nature of decentralized datasets and the robustnes...

0 Chenyang Ma, et al. ∙

research

∙ 02/15/2023

A Federated Learning Benchmark for Drug-Target Interaction

Aggregating pharmaceutical data in the drug-target interaction (DTI) dom...

0 Gianluca Mittone, et al. ∙

research

∙ 12/15/2022

NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution

In recent years, image and video delivery systems have begun integrating...

0 Stylianos I. Venieris, et al. ∙

research

∙ 12/15/2022

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation

Recent image degradation estimation methods have enabled single-image su...

0 Royson Lee, et al. ∙

research

∙ 11/30/2022

Pex: Memory-efficient Microcontroller Deep Learning through Partial Execution

Embedded and IoT devices, largely powered by microcontroller units (MCUs...

0 Edgar Liberis, et al. ∙

research

∙ 10/19/2022

The Future of Consumer Edge-AI Computing

Deep Learning has proliferated dramatically across consumer devices in l...

0 Stefanos Laskaridis, et al. ∙

research

∙ 09/30/2022

Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio

Self-supervised learning (SSL) has proven vital in speech and audio-rela...

11 Yan Gao, et al. ∙

research

∙ 09/27/2022

Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs

With deep neural networks (DNNs) emerging as the backbone in a multitude...

0 Alexandros Kouris, et al. ∙

research

∙ 09/20/2022

Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design

Attention-based neural networks have become pervasive in many AI tasks. ...

6 Hongxiang Fan, et al. ∙

research

∙ 07/03/2022

Protea: Client Profiling within Federated Systems using Flower

Federated Learning (FL) has emerged as a prospective solution that facil...

2 Wanru Zhao, et al. ∙

research

∙ 05/19/2022

Multi-DNN Accelerators for Next-Generation AI Systems

As the use of AI-powered applications widens across multiple domains, so...

0 Stylianos I. Venieris, et al. ∙

research

∙ 05/12/2022

Secure Aggregation for Federated Learning in Flower

Federated Learning (FL) allows parties to learn a shared prediction mode...

0 Kwing Hei Li, et al. ∙

research

∙ 04/06/2022

Federated Self-supervised Speech Representations: Are We There Yet?

The ubiquity of microphone-enabled devices has lead to large amounts of ...

5 Yan Gao, et al. ∙

research

∙ 10/26/2021

Defensive Tensorization

We propose defensive tensorization, an adversarial defence technique tha...

4 Adrian Bulat, et al. ∙

research

∙ 10/15/2021

Differentiable Network Pruning for Microcontrollers

Embedded and personal IoT devices are powered by microcontroller units (...

0 Edgar Liberis, et al. ∙

research

∙ 09/28/2021

Smart at what cost? Characterising Mobile Deep Neural Networks in the wild

With smartphones' omnipresence in people's pockets, Machine Learning (ML...

0 Mario Almeida, et al. ∙

research

∙ 09/08/2021

AgreementLearning: An End-to-End Framework for Learning with Multiple Annotators without Groundtruth

The annotation of domain experts is important for some medical applicati...

12 Chongyang Wang, et al. ∙

research

∙ 08/18/2021

Temporal Kernel Consistency for Blind Video Super-Resolution

Deep learning-based blind super-resolution (SR) methods have recently ac...

6 Lichuan Xiang, et al. ∙

research

∙ 06/12/2021

Zero-Cost Proxies Meet Differentiable Architecture Search

Differentiable neural architecture search (NAS) has attracted significan...

4 Lichuan Xiang, et al. ∙

research

∙ 06/09/2021

Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions

DNNs are becoming less and less over-parametrised due to recent advances...

0 Stefanos Laskaridis, et al. ∙

research

∙ 06/07/2021

Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions

Internet-enabled smartphones and ultra-wide displays are transforming a ...

0 Royson Lee, et al. ∙

research

∙ 06/07/2021

Multi-Exit Semantic Segmentation Networks

Semantic segmentation arises as the backbone of many vision systems, spa...

0 Alexandros Kouris, et al. ∙

research

∙ 04/29/2021

End-to-End Speech Recognition from Federated Acoustic Models

Training Automatic Speech Recognition (ASR) models under federated learn...

0 Yan Gao, et al. ∙

research

∙ 04/20/2021

DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device

Recently, there has been an explosive growth of mobile and embedded appl...

0 Mario Almeida, et al. ∙

research

∙ 04/07/2021

On-device Federated Learning with Flower

Federated Learning (FL) allows edge devices to collaboratively learn a s...

18 Akhil Mathur, et al. ∙

research

∙ 04/03/2021

Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions

Training and deploying graph neural networks (GNNs) remains difficult du...

0 Shyam A. Tailor, et al. ∙

research

∙ 03/09/2021

unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation

Single computation engines have become a popular design choice for FPGA-...

0 Stylianos I. Venieris, et al. ∙

research

∙ 02/26/2021

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

Federated Learning (FL) has been gaining significant traction across dif...

0 Samuel Horvath, et al. ∙

research

∙ 02/02/2021

It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation

On-device machine learning is becoming a reality thanks to the availabil...

0 Ilias Leontiadis, et al. ∙

research

∙ 01/20/2021

Zero-Cost Proxies for Lightweight NAS

Neural Architecture Search (NAS) is quickly becoming the standard method...

14 Mohamed S. Abdelfattah, et al. ∙

research

∙ 11/03/2020

Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data

Protective behavior exhibited by people with chronic pain (CP) during ph...

4 Chongyang Wang, et al. ∙

research

∙ 10/27/2020

μNAS: Constrained Neural Architecture Search for Microcontrollers

IoT devices are powered by microcontroller units (MCUs) which are extrem...

0 Edgar Liberis, et al. ∙

research

∙ 10/17/2020

Deep Learning in the Era of Edge Computing: Challenges and Opportunities

The era of edge computing has arrived. Although the Internet is the back...

74 Mi Zhang, et al. ∙

research

∙ 10/13/2020

A first look into the carbon footprint of federated learning

Despite impressive results, deep learning-based technologies also raise ...

4 Xinchi Qiu, et al. ∙

research

∙ 10/12/2020

Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions

Internet-enabled smartphones and ultra-wide displays are transforming a ...

0 Royson Lee, et al. ∙

research

∙ 09/06/2020

Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation

This paper introduces a new dataset, Libri-Adapt, to support unsupervise...

0 Akhil Mathur, et al. ∙

research

∙ 08/14/2020

SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud

Despite the soaring use of convolutional neural networks (CNNs) in mobil...

9 Stefanos Laskaridis, et al. ∙

research

∙ 08/11/2020

Degree-Quant: Quantization-Aware Training for Graph Neural Networks

Graph neural networks (GNNs) have demonstrated strong performance on a w...

0 Shyam A. Tailor, et al. ∙

research

∙ 08/11/2020

Bunched LPCNet : Vocoder for Low-cost Neural Text-To-Speech Systems

LPCNet is an efficient vocoder that combines linear prediction and deep ...

0 Ravichander Vipperla, et al. ∙

research

∙ 08/10/2020

HAPI: Hardware-Aware Progressive Inference

Convolutional neural networks (CNNs) have recently become the state-of-t...

9 Stefanos Laskaridis, et al. ∙

Nicholas D. Lane

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