machine learning – Page 36 – Andrew Fairless, Ph.D.

What I Read: Prompting, Language Models, NLP

By Andrew Fairless on August 9, 2021July 22, 2021

https://thegradient.pub/prompting/ Prompting: Better Ways of Using Language Models for NLP Tasks03.Jul.2021Tianyu Gao “The giant model size of GPT-3 is an important factor for its success, while the concept of promptsContinue readingWhat I Read: Prompting, Language Models, NLP

What I Read: Gradient Pseudo-Swap

By Andrew Fairless on August 3, 2021July 12, 2021

https://deepnote.com/@martin-molnar/Gradient-Pseudo-Swap-F2u_aTbqTOisNYCH_JORwg Martin MolnarGradient Pseudo-Swap “When we have layers in a neural network we want to train with gradient descent, but those layers don’t have smooth gradients that can be used,Continue readingWhat I Read: Gradient Pseudo-Swap

What I Read: SwAV method

By Andrew Fairless on August 2, 2021July 12, 2021

https://m0nads.wordpress.com/2021/01/08/the-swav-method/ The SwAV methodAntonio Ferraioli “The SwAV method is a clustering-based online method whose goal is to learn visual features in an online fashion without supervision.”

What I Read: CNN Heat Maps, Class Activation Mapping

By Andrew Fairless on July 30, 2021July 12, 2021

https://glassboxmedicine.com/2019/06/11/cnn-heat-maps-class-activation-mapping-cam/ CNN Heat Maps: Class Activation Mapping (CAM)Date: June 11, 2019Author: Rachel Draelos “Class Activation Mapping (CAM) is one technique for producing heat maps to highlight class-specific regions of images.”

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: Parallelizing neural networks, GPU, JAX

By Andrew Fairless on July 28, 2021July 12, 2021

https://willwhitney.com/parallel-training-jax.html Will WhitneyParallelizing neural networks on one GPU with JAX How you can get a 100x speedup for training small neural networks by making the most of your accelerator.“Most neuralContinue readingWhat I Read: Parallelizing neural networks, GPU, JAX

What I Read: Better computer vision models, Transformers, CNNs

By Andrew Fairless on July 27, 2021July 12, 2021

https://ai.facebook.com/blog/computer-vision-combining-transformers-and-convolutional-neural-networks/ Better computer vision models by combining Transformers and convolutional neural networksJuly 8, 2021 “We’ve developed a new computer vision model… which combines… convolutional neural networks (CNNs) and Transformer-based models…Continue readingWhat I Read: Better computer vision models, Transformers, CNNs

What I Read: Model Free

By Andrew Fairless on July 26, 2021July 12, 2021

http://www.argmin.net/2018/04/19/pid/ The Best Things in Life Are Model FreeBen RechtApr 19, 2018 “The odd thing about statistics and ML research these days is that everyone knows about gradient descent, butContinue readingWhat I Read: Model Free

What I Read: Causal Inference, Elasticity Pricing

By Andrew Fairless on July 23, 2021July 12, 2021

https://towardsdatascience.com/causal-inference-example-elasticity-de4a3e2e621b?gi=cb88b072c5b9 Causal Inference in the Wild: Elasticity PricingHow can machine learning to improve causal inference in industry? I describe a real example with code for retail pricing.Lars RoemheldJuly 8, 2021Continue readingWhat I Read: Causal Inference, Elasticity Pricing

What I Read: Double Machine Learning for causal inference

By Andrew Fairless on July 21, 2021July 2, 2021

https://towardsdatascience.com/double-machine-learning-for-causal-inference-78e0c6111f9d Double Machine Learning for causal inferenceHow Double Machine Learning for causal inference works, from the theoretical foundations to an example of application.Borja VelascoJun 25 “This post tries to explain,Continue readingWhat I Read: Double Machine Learning for causal inference

Tag: machine learning