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Found 3 papers, 2 papers with code
Series of Hessian-Vector Products for Tractable Saddle-Free Newton Optimisation of Neural Networks
A truncation of this infinite series provides a new optimisation algorithm which is scalable and comparable to other first- and second-order optimisation methods in both runtime and optimisation performance.
Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners
This paper examines the robustness of deployed few-shot meta-learning systems when they are fed an imperceptibly perturbed few-shot dataset.
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation
Machine learning training methods depend plentifully and intricately on hyperparameters, motivating automated strategies for their optimisation.
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