Nicholas Donald Lane

Artificial Intelligence · 2006–2021

A researcher in the Science corpus: 21 papers; trusts 394 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 247 citations into it
Computer Vision and Pattern Recognition — 182 citations into it; #5,764 of 21,575 by trust here, #2,872 by citations
Computer Networks and Communications — 67 citations into it; #6,206 of 9,886 by trust here, #677 by citations
Efficiency & Compression — 63 citations into it
Signal Processing — 63 citations into it; #3,608 of 7,572 by trust here, #1,958 by citations
Federated & Distributed Learning — 45 citations into it
Optimization & Training — 44 citations into it
Electrical and Electronic Engineering — 37 citations into it

Whom Nicholas Donald Lane trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Nicholas Donald Lane overall

Papers from Nicholas Donald Lane's perspective

Ordered by how strongly the researchers Nicholas Donald Lane trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Long Short-Term Memory
Gradient-based learning applied to document recognition
Attention is All you Need (Neural Information Processing Systems)
ImageNet: A large-scale hierarchical image database
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Learning Multiple Layers of Features from Tiny Images

Their papers

SoundSense: scalable sound sensing for people-centric applications on mobile phones (2009) — 688 citations
Zero-Cost Proxies for Lightweight NAS (2021) — 352 citations
MoodScope: building a mood sensor from smartphone usage patterns (2013) — 544 citations
Bewell: A smartphone application to monitor, model and promote wellbeing (2011) — 469 citations
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout (2021) — 365 citations
Flower: A Friendly Federated Learning Research Framework (2020) — 1,331 citations
Bunched LPCNet : Vocoder for Low-cost Neural Text-To-Speech Systems (2020) — 27 citations
A first look into the carbon footprint of federated learning (2020) — 122 citations
SPINN: synergistic progressive inference of neural networks over device and cloud (2020) — 364 citations
An Empirical study of Binary Neural Networks' Optimisation (2018) — 96 citations
Accelerating Mobile Audio Sensing Algorithms through On-Chip GPU Offloading (2017) — 22 citations
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics (2017) — 266 citations
DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices (2016) — 568 citations
Using Smartphones to Collect Behavioral Data in Psychological Science: Opportunities, Practical Considerations, and Challenges (2016) — 454 citations
DeepEar: robust smartphone audio sensing in unconstrained acoustic environments using deep learning (2015) — 335 citations
An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices (2015) — 220 citations
Urban sensing systems: opportunistic or participatory? (2008) — 305 citations
Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application (2008) — 1,219 citations
The BikeNet mobile sensing system for cyclist experience mapping (2007) — 554 citations
People-centric urban sensing (2006) — 514 citations