Zobrazeno 1 - 10
of 480
pro vyhledávání: '"Gordon Cameron"'
Low-rank decomposition has emerged as a vital tool for enhancing parameter efficiency in neural network architectures, gaining traction across diverse applications in machine learning. These techniques significantly lower the number of parameters, st
Externí odkaz:
http://arxiv.org/abs/2403.19243
Deep implicit functions have been found to be an effective tool for efficiently encoding all manner of natural signals. Their attractiveness stems from their ability to compactly represent signals with little to no offline training data. Instead, the
Externí odkaz:
http://arxiv.org/abs/2403.19163
In this article we show that all cyclic branched covers of a Seifert link have left-orderable fundamental groups, and therefore admit co-oriented taut foliations and are not $L$-spaces, if and only if it is not an $ADE$ link up to orientation. This l
Externí odkaz:
http://arxiv.org/abs/2402.15914
We empirically show that process-based Parallelism speeds up the Genetic Algorithm (GA) for Feature Selection (FS) 2x to 25x, while additionally increasing the Machine Learning (ML) model performance on metrics such as F1-score, Accuracy, and Receive
Externí odkaz:
http://arxiv.org/abs/2401.10846
In this article, we apply slope detection techniques to study properties of toroidal $3$-manifolds obtained by performing Dehn surgeries on satellite knots in the context of the $L$-space conjecture. We show that if $K$ is an $L$-space knot or admits
Externí odkaz:
http://arxiv.org/abs/2307.06815
In this paper we study the left-orderability of $3$-manifold groups using an enhancement, called recalibration, of Calegari and Dunfield's "flipping" construction, used for modifying $\mbox{Homeo}_+(S^1)$-representations of the fundamental groups of
Externí odkaz:
http://arxiv.org/abs/2306.10357
Autor:
Gordon, Cameron
The hierarchical nature of corporate information processing is a topic of great interest in economic and management literature. Firms are characterised by a need to make complex decisions, often aggregating partial and uncertain information, which gr
Externí odkaz:
http://arxiv.org/abs/2210.14861