learning – Andrew Fairless, Ph.D.

What I Read: Neuron Bursts Can Mimic Famous AI Learning Strategy

By Andrew Fairless on November 1, 2021October 24, 2021

https://www.quantamagazine.org/brain-bursts-can-mimic-famous-ai-learning-strategy-20211018/ Neuron Bursts Can Mimic Famous AI Learning StrategyAllison WhittenOctober 18, 2021“A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation,Continue readingWhat I Read: Neuron Bursts Can Mimic Famous AI Learning Strategy

What I Read: Geometric, Deep Learning

By Andrew Fairless on August 16, 2021July 22, 2021

https://towardsdatascience.com/geometric-foundations-of-deep-learning-94cdd45b451d?gi=d7fa7307aa63 Geometric foundations of Deep LearningGeometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. These principlesContinue readingWhat I Read: Geometric, Deep Learning

What I Read: Representation quality, complexity

By Andrew Fairless on July 29, 2021July 12, 2021

https://willwhitney.com/representation-quality-and-the-complexity-of-learning.html Will WhitneyRepresentation quality and the complexity of learning “In the last few years, there’s been an explosion of work on learning good representations of data…. However, defining precisely whatContinue readingWhat I Read: Representation quality, complexity

What I Read: Flows for simultaneous manifold learning and density estimation

By Andrew Fairless on December 31, 2020December 20, 2020

https://arxiv.org/abs/2003.13913 Flows for simultaneous manifold learning and density estimationJohann Brehmer, Kyle Cranmer “We introduce manifold-learning flows (M-flows), a new class of generative models that simultaneously learn the data manifold asContinue readingWhat I Read: Flows for simultaneous manifold learning and density estimation

What I Read: To Adapt to Tech, We’re Heading Into the Shadows

By Andrew Fairless on December 30, 2020December 20, 2020

https://www.wired.com/story/opinion-to-adapt-to-tech-were-heading-into-the-shadows/ Matt BeaneIdeas06.08.2020 09:59 AMTo Adapt to Tech, We’re Heading Into the ShadowsMore and more innovation requires going into darker, more inappropriate, less ethical territory. Here’s how to respond. “…I’veContinue readingWhat I Read: To Adapt to Tech, We’re Heading Into the Shadows

What I Read: Diffusion Map for manifold learning

By Andrew Fairless on December 19, 2020December 8, 2020

https://randomwalk.in/python/ml/2020/03/14/Diffusion-Map.html Diffusion Map for manifold learning, Theory and Implementation “Manifold learning is an approach to non-linear dimensionality reduction…. In this blog, we learn one of the many techniques in manifoldContinue readingWhat I Read: Diffusion Map for manifold learning

Tag: learning