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 (2): The Dogma of Sparsity

· Read in · 1700 words · collected posts · [dropcap]The[/dropcap] functioning of our brains, much like the intrigue of a political drama, is a neuronal house-of-cards. The halls of cognitive power are run by recurring alliances of neurons that deliberately conspire to control information processing and decision … Continue reading Learning in Brains and Machines (2): The Dogma of Sparsity

Bayesian sparsity using spike-and-slab priors

I recently received some queries on our paper: S. Mohamed, K. Heller and Z. Ghahramani. Bayesian and L1 Approaches for Sparse Unsupervised Learning. International Conference on Machine Learning (ICML), June 2012 [cite key="mohamed2012sparse"]. The questions were very good and I thought it would be useful to post these for future reference. The paper looked at Bayesian and optimisation approaches for learning sparse models. For Bayesian models, we advocated the use of spike-and-slab sparse models and specified an adapted latent Gaussian model with an additional set of discrete latent variables to specify when a latent dimension is sparse or not. This … Continue reading Bayesian sparsity using spike-and-slab priors