5 citations · 10 across the 8 of their papers we have counts for
9 papers · 1 filter
Magnitude Distance: A Geometric Measure of Dataset Similarity
Sahel Torkamani, Henry Gouk, Rik Sarkar
Quantifying the distance between datasets is a fundamental question in mathematics and machine learning. We propose \textit{magnitude distance}, a novel distance metric defined on…
Computing Strategic Responses to Non-Linear Classifiers
Jack Geary, Boyan Gao, Henry Gouk
We consider the problem of strategic classification, where the act of deploying a classifier leads to strategic behaviour that induces a distribution shift on subsequent observatio…
Model Diffusion for Certifiable Few-shot Transfer Learning
Fady Rezk, Royson Lee, Henry Gouk +2
In contemporary deep learning, a prevalent and effective workflow for solving low-data problems is adapting powerful pre-trained foundation models (FMs) to new tasks via parameter-…
Strategic Classification with Randomised Classifiers
Jack Geary, Henry Gouk
We consider the problem of strategic classification, where a learner must build a model to classify agents based on features that have been strategically modified. Previous work in…
Meta Mirror Descent: Optimiser Learning for Fast Convergence
Boyan Gao, Henry Gouk, Hae Beom Lee +1
Optimisers are an essential component for training machine learning models, and their design influences learning speed and generalisation. Several studies have attempted to learn m…
Searching for Robustness: Loss Learning for Noisy Classification Tasks
Boyan Gao, Henry Gouk, Timothy M. Hospedales
We present a "learning to learn" approach for automatically constructing white-box classification loss functions that are robust to label noise in the training data. We parameteriz…