Learning in Brains and Machines (4): Episodic and Interactive Memory

· Read in · 2080 words · All posts in series  · [dropcap]My[/dropcap] memory, like yours, exerts a powerful influence over my interaction with the world. It is reconstructive and evocative; I can easily form an image of hot December days in the South African summer, and remember my first time—it was … Continue reading Learning in Brains and Machines (4): Episodic and Interactive Memory

Learning in Brains and Machines (3): Synergistic and Modular Action

· Read in · 1796 words · All posts in series  · [dropcap]There[/dropcap] is a dance—precisely choreographed and executed—that we perform throughout our lives. This is the dance formed by our movements. Our movements are our actions and the final outcome of our decision making processes. Single actions are … Continue reading Learning in Brains and Machines (3): Synergistic and Modular Action

Machine Learning Trick of the Day (5): Log Derivative Trick

Machine learning involves manipulating probabilities. These probabilities are most often represented as normalised-probabilities or as log-probabilities. An ability to shrewdly alternate between these two representations is a vital step towards strengthening the probabilistic dexterity we need to solve modern machine learning problems. Today's trick, the log derivative trick, helps … Continue reading Machine Learning Trick of the Day (5): Log Derivative Trick

Machine Learning Trick of the Day (4): Reparameterisation Tricks

Our ability to rewrite statistical problems in an equivalent but different form, to reparameterise them, is one of the most general-purpose tools we have in mathematical statistics. We used reparameterisation in all the tricks we explored in this series so far: trick 1 re-expressed a … Continue reading Machine Learning Trick of the Day (4): Reparameterisation Tricks