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pro vyhledávání: '"Marchesotti, Nicolas"'
The demand for open and trustworthy AI models points towards widespread publishing of model weights. Consumers of these model weights must be able to act accordingly with the information provided. That said, one of the simplest AI classification mode
Externí odkaz:
http://arxiv.org/abs/2406.13427
Autor:
Acero, Fernando, Zehtabi, Parisa, Marchesotti, Nicolas, Cashmore, Michael, Magazzeni, Daniele, Veloso, Manuela
Portfolio optimization involves determining the optimal allocation of portfolio assets in order to maximize a given investment objective. Traditionally, some form of mean-variance optimization is used with the aim of maximizing returns while minimizi
Externí odkaz:
http://arxiv.org/abs/2403.16667
We introduce a family of interpretable machine learning models, with two broad additions: Linearised Additive Models (LAMs) which replace the ubiquitous logistic link function in General Additive Models (GAMs); and SubscaleHedge, an expert advice alg
Externí odkaz:
http://arxiv.org/abs/2211.06360
Publikováno v:
Presented at ICLR 2022 Workshop on Socially Responsible Machine Learning
Concept bottleneck models perform classification by first predicting which of a list of human provided concepts are true about a datapoint. Then a downstream model uses these predicted concept labels to predict the target label. The predicted concept
Externí odkaz:
http://arxiv.org/abs/2211.03656