Posts & Shots

Notes On Concurrency In Jvm

introduction to concurrency in jvm

Notes On Concurrency In Jvm

introduction to concurrency in jvm

Softmax Regression Revisit 2

sampling based approaches to reduce the computational complexity in the gradient calculation of the softmax regression.

Softmax Regression Revisit 2

sampling based approaches to reduce the computational complexity in the gradient calculation of the softmax regression.

Softmax Regression Revisit

revisit on softmax regression, including derivation in details and hierarchical softmax regression.

Softmax Regression Revisit

revisit on softmax regression, including derivation in details and hierarchical softmax regression.

Notes On Differentiation

notes on differentiations, including the numerical differentiation, the forward-mode differentiation, and the reverse-mode differentiation

Notes On Differentiation

notes on differentiations, including the numerical differentiation, the forward-mode differentiation, and the reverse-mode differentiation

Classnotfoundexception Vs Noclassdeffounderror

It has been a while not updating notes. It feels good to get rid of that shit project. This note is about two exceptions that are mingled by many people: ClassNotFoundException and NoClassDefFoundError.

Classnotfoundexception Vs Noclassdeffounderror

It has been a while not updating notes. It feels good to get rid of that shit project. This note is about two exceptions that are mingled by many people: ClassNotFoundException and NoClassDefFoundError.

Notes On The Isotonic Regression

The isotonic regression is used to fit monotonic curve, and classifier calibration is a typical use case.

Notes On The Isotonic Regression

The isotonic regression is used to fit monotonic curve, and classifier calibration is a typical use case.

Notes On Ensembles Of Decision Trees

Introduction to the random forest decision tree, the gradient boosting regression tree, and the adaptive boosting classification tree.

Notes On Ensembles Of Decision Trees

Introduction to the random forest decision tree, the gradient boosting regression tree, and the adaptive boosting classification tree.

Notes On Classification And Regression Trees

A very rough view on the CART, without the mention of implementation details.

Notes On Classification And Regression Trees

A very rough view on the CART, without the mention of implementation details.

Notes On Significance Test Revisit

The type I error, the type II error, and some other concepts in the significance test.

Notes On Significance Test Revisit

The type I error, the type II error, and some other concepts in the significance test.