5 citations · 6 across the 7 of their papers we have counts for
5 papers · 1 filter
Trust Region On-Policy Distillation
Xingrun Xing, Haoqing Wang, Boyan Gao +2
On-Policy Distillation (OPD) is a fundamental technique for efficient post-training of large language models (LLMs), with broad applications in agent learning, multi-task enhanceme…
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…
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…
Deep clustering with concrete k-means
Boyan Gao, Yongxin Yang, Henry Gouk +1
We address the problem of simultaneously learning a k-means clustering and deep feature representation from unlabelled data, which is of interest due to the potential of deep k-mea…