106 citations · 259 across the 30 of their papers we have counts for
7 papers · 1 filter
Defensive Tensorization
Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya +5
We propose defensive tensorization, an adversarial defence technique that leverages a latent high-order factorization of the network. The layers of a network are first expressed as…
Differentiable Network Pruning for Microcontrollers
Edgar Liberis, Nicholas D. Lane
Embedded and personal IoT devices are powered by microcontroller units (MCUs), whose extreme resource scarcity is a major obstacle for applications relying on on-device deep learni…
Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth
Chongyang Wang, Yuan Gao, Chenyou Fan +4
The annotation of domain experts is important for some medical applications where the objective ground truth is ambiguous to define, e.g., the rehabilitation for some chronic disea…
A Channel Coding Benchmark for Meta-Learning
Rui Li, Ondrej Bohdal, Rajesh Mishra +4
Meta-learning provides a popular and effective family of methods for data-efficient learning of new tasks. However, several important issues in meta-learning have proven hard to st…
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions
Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane
DNNs are becoming less and less over-parametrised due to recent advances in efficient model design, through careful hand-crafted or NAS-based methods. Relying on the fact that not…
Zero-Cost Operation Scoring in Differentiable Architecture Search
Lichuan Xiang, Łukasz Dudziak, Mohamed S. Abdelfattah +3
We formalize and analyze a fundamental component of differentiable neural architecture search (NAS): local "operation scoring" at each operation choice. We view existing operation…
Do We Need Anisotropic Graph Neural Networks?
Shyam A. Tailor, Felix L. Opolka, Pietro Liò +1
Common wisdom in the graph neural network (GNN) community dictates that anisotropic models -- in which messages sent between nodes are a function of both the source and target node…