Machine Learning

2 Bayesian Linear Regression

#Machine Learning #Regression #Bayesian

Bayesian Linear Regression

2 NMF: Nonnegative Matrix Factorizatioin

#Machine Learning #Factorization

Nonnegative Matrix Factorizatioin has a bright future

2 Word2vec

#Machine Learning #Embedding #Word2vec

Single-layer neural network creates embedding space

2 Bias-Variance

#Statistical Learning #Basics

Bias Variance Trade off is a key concept in statistical learning

2 Unsupervised Learning: PCA

#PCA #Unsupervised Learning #Statistical Learning #Basics

Principal component analysis is a method to remove redundancies of the features by looking into the variances.

3 Contrastive Model: Instance-Instance

#Self-supervised Learning #Contrastive Model #Basics

It was discovered that the success of [[mutual information based contrastive learning]] Contrastive …

3 Generative Model: Normalizing Flow

#Self-supervised Learning #Generative Model #Normalizing Flow #Basics

Normalizing flow is a method to convert a complicated distribution $p(x)$ to a simpler distribution …

3 infoGAN

#Self-supervised Learning #Adversarial Model #GAN #Basics

In GAN, the latent space input is usually random noise, e.g., Gaussian noise. The objective of …

3 Logistic Regression

#Unsupervised Learning #Statistical Learning #Basics #Linear Models #Supervised Learning #Classification

logistics regression is a simple model for classification

3 Random Forest

#Decision Tree #Ensemble #Supervised Learning #Statistical Learning #Basics

random forest in machine learning

3 Tensor Factorization

#Machine Learning #Factorization #Tensor

A generalization of matrix factorization

3 Unsupervised Learning: SVM

#SVM #Unsupervised Learning #Statistical Learning #Basics

unsupervised learning: support vector machine

4 Contrastive Predictive Coding

#Self-supervised Learning #Contrastive Model #Mutual Information #Contrastive #Predictive Coding #Basics

Contrastive Predictive Coding, aka CPC, is an autoregressive model combined with InfoNCE loss1. …

4 Deep Infomax

#Self-supervised Learning #Contrastive Model #Mutual Information #Deep Infomax #Basics

Max Global Mutual Information Why not just use the global mutual information of the input and …

4 Generative Model: Auto-Encoder

#Self-supervised Learning #Generative Model #Auto-Encoder #Basics

Autoencoders (AE) are machines that encodes inputs into a compact latent space. The simplest …

4 Deep Autoregressive Network

#Machine Learning #Autoregressive Network

DARN

5 Variational Auto-Encoder

#Self-supervised Learning #Generative Model #VAE #Basics

In an inference problem, $p(z\vert x)$, which is used to infer $z$ from $x$. $$ p(z\vert x) = …

5 Layer Norm

#Machine Learning

Layer norm

6 Batch Norm

#Machine Learning

Batch norm

Centered Kernel Alignment (CKA)

#Data #Representation #Similarity

Centered Kernel Alignment (CKA) is a similarity metric designed to measure the similarity of between representations of features in neural networks.