
MetropolisHastings Algorithm

BoxMuller Algorithm

From RankNet to LambdaRank to LambdaMART: An Overview (2010)

ListNet: A Listwise Approach of Learning to Rank (2007)

Notes on zkSNARKs in Nutshell

CycleGAN

Binomial confidence interval

Reinforcement Learning 17: Frontiers

Reinforcement Learning 16: Applications and Case Studies

Reinforcement Learning 15: Neuroscience

Reinforcement Learning 14: Psychology

Reinforcement Learning 13: Policy Gradient Methods

Reinforcement Learning: Models

Reinforcement Learning 12: Eligibility Traces

Statistical Inference 9~12

Interesting interview algorithm problems

RCNN

YOLO

Reinforcement Learning 11: Offpolicy Methods with Approximation

Y Combinator 精简版

Reinforcement Learning 10: Onpolicy Control with Approximation

Attention Models

AlphaGo(Zero) 学习笔记

Capsule Network

Wasserstein GAN

Reinforcement Learning 9: Onpolicy Prediction with Approximation

Reinforcement Learning 8: Planning and Learning with Tabular Methods

Reinforcement Learning 7: nstep Bootstrapping

Reinforcement Learning 6: TemporalDifference Learning

Reinforcement Learning 5: Monte Carlo Methods

Reinforcement Learning 4: Dynamic Programming

FractalNet

Y Combinator

Reinforcement Learning 3: Finite Markov Decision Processes

圣彼得堡悖论 II

Reinforcement Learning 2: Multiarmed Bandits

Reinforcement Learning 1: Introduction

Deep Learning: Chapter 20

Deep Learning: Chapter 19

Deep Learning: Chapter 18

Deep Learning: Chapter 17

Deep Learning: Chapter 16

Deep Learning: Chapter 15

Deep Learning: Chapter 14

Deep Learning: Chapter 13

Deep Learning: Chapter 12

Deep Learning: Chapter 11

Deep Learning: Chapter 10

变分推断

LightRNN

Deep Learning: Chapter 9

Deep Learning: Chapter 8

Deep Learning: Chapter 7

机器学习 Tom 1~4

Deep Learning: Chapter 6

Deep Learning: Chapter 5

CS224n: NLP with Deep Learning

Fourier Transform

The Elements of Statistical Learning

Practical Foundations for Programming Languages 1

Algorithms for Big Data

Geometric Approximation Algorithms

代数学引论 第一卷

Copernican Principle

Statistical Inference 5~8

信息论基础 9~17

复分析基础及工程应用 习题

复分析基础及工程应用

Statistical Inference 1~4

Learning Asymptote

信息论基础 1~8

The Design of Approximation Algorithms

圣彼得堡悖论

数学分析原理

Problem Set
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