Tags

keep hungry keep foolish
经典机器学习

决策树之三-CART

决策树之二-ID3与C4.5

决策树之一-基础篇

蒙特卡罗方法简介

Logistic 回归简介

Logistic Regression

机器学习

SMART 介绍

Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

MacBERT 介绍

Revisiting Pre-trained Models for Chinese Natural Language Processing

HDBSCAN 简介

一种基于密度的聚类方法

ALBERT 介绍

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS

ERNIE 介绍

Enhanced Representation through Knowledge Integration

DBSCAN 简介

一种基于密度的聚类方法

TinyBERT 介绍

Distilling BERT for Natural Language Understanding

K-Means 简介

一种基于质心的聚类方法

RoBERTa 介绍

A Robustly Optimized BERT Pretraining Approach

聚类简介

知识生产和数据挖掘利器

BERT 介绍

Pre-training of Deep Bidirectional Transformers for Language Understanding

Transformer 介绍

Attention Is All You Need

COMET 介绍

Commonsense Transformers for Automatic Knowledge Graph Construction

ConvLab 代码解读

DSTC8 对话评测代码框架

DialogFlow 试用

一个很好的对话机器人产品化的例子

微软小冰解读

The Design and Implementation of XiaoIce, an Empathetic Social Chatbot

FGM 介绍

ADVERSARIAL TRAINING METHODS FOR SEMI-SUPERVISED TEXT CLASSIFICATION

FGSM 介绍

EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES

Temporal Ensembling 介绍

TEMPORAL ENSEMBLING FOR SEMI-SUPERVISED LEARNING

Mean Teacher 介绍

Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

VisualBERT 介绍

A SIMPLE AND PERFORMANT BASELINE FOR VISION AND LANGUAGE

VideoBERT 介绍

A Joint Model for Video and Language Representation Learning

LXMERT 介绍

Learning Cross-Modality Encoder Representations from Transformers

Boostring 介绍

提升方法，包括AdaBoost/GBDT/XGBoost等

Bagging 介绍

一种简单有效的集成学习方法

TranE 介绍

Translating Embeddings for Modeling Multi-relational Data

Label Smoothing 介绍

超级简单的模型正则化方法，还不赶快炼丹试试

DropConnect 介绍

Regularization of Neural Networks using DropConnect

Dropout 介绍

A Simple Way to Prevent Neural Networks from Overfitting

决策树之三-CART

决策树之二-ID3与C4.5

决策树之一-基础篇

蒙特卡罗方法简介

Logistic 回归简介

Logistic Regression

CPP

C++11 并发编程之五 - future

C++11 并发编程之四 - thread

C++11 并发编程之三 - condition_variable

C++11 并发编程之二 - mutex

C++11 并发编程之一 - atomic

排序算法汇总

算法与数据结构

排序算法汇总

模型正则化

FGM 介绍

ADVERSARIAL TRAINING METHODS FOR SEMI-SUPERVISED TEXT CLASSIFICATION

FGSM 介绍

EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES

Temporal Ensembling 介绍

TEMPORAL ENSEMBLING FOR SEMI-SUPERVISED LEARNING

Mean Teacher 介绍

Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Label Smoothing 介绍

超级简单的模型正则化方法，还不赶快炼丹试试

DropConnect 介绍

Regularization of Neural Networks using DropConnect

Dropout 介绍

A Simple Way to Prevent Neural Networks from Overfitting

自然语言处理

SMART 介绍

Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

MacBERT 介绍

Revisiting Pre-trained Models for Chinese Natural Language Processing

ALBERT 介绍

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS

ERNIE 介绍

Enhanced Representation through Knowledge Integration

TinyBERT 介绍

Distilling BERT for Natural Language Understanding

RoBERTa 介绍

A Robustly Optimized BERT Pretraining Approach

BERT 介绍

Pre-training of Deep Bidirectional Transformers for Language Understanding

Transformer 介绍

Attention Is All You Need

COMET 介绍

Commonsense Transformers for Automatic Knowledge Graph Construction

ConvLab 代码解读

DSTC8 对话评测代码框架

DialogFlow 试用

一个很好的对话机器人产品化的例子

微软小冰解读

The Design and Implementation of XiaoIce, an Empathetic Social Chatbot

FGM 介绍

ADVERSARIAL TRAINING METHODS FOR SEMI-SUPERVISED TEXT CLASSIFICATION

TranE 介绍

Translating Embeddings for Modeling Multi-relational Data

知识图谱

COMET 介绍

Commonsense Transformers for Automatic Knowledge Graph Construction

TranE 介绍

Translating Embeddings for Modeling Multi-relational Data

集成学习

Boostring 介绍

提升方法，包括AdaBoost/GBDT/XGBoost等

Bagging 介绍

一种简单有效的集成学习方法

计算机基础

Markdown 常用功能介绍

一起写博客吧

Latex 常用数学符号

一起写博客吧

多模态

VisualBERT 介绍

A SIMPLE AND PERFORMANT BASELINE FOR VISION AND LANGUAGE

VideoBERT 介绍

A Joint Model for Video and Language Representation Learning

LXMERT 介绍

Learning Cross-Modality Encoder Representations from Transformers

BERT

MacBERT 介绍

Revisiting Pre-trained Models for Chinese Natural Language Processing

ALBERT 介绍

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS

ERNIE 介绍

Enhanced Representation through Knowledge Integration

TinyBERT 介绍

Distilling BERT for Natural Language Understanding

RoBERTa 介绍

A Robustly Optimized BERT Pretraining Approach

BERT 介绍

Pre-training of Deep Bidirectional Transformers for Language Understanding

Transformer 介绍

Attention Is All You Need

VisualBERT 介绍

A SIMPLE AND PERFORMANT BASELINE FOR VISION AND LANGUAGE

VideoBERT 介绍

A Joint Model for Video and Language Representation Learning

LXMERT 介绍

Learning Cross-Modality Encoder Representations from Transformers

半监督学习

Temporal Ensembling 介绍

TEMPORAL ENSEMBLING FOR SEMI-SUPERVISED LEARNING

Mean Teacher 介绍

Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

对抗学习

SMART 介绍

Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

FGM 介绍

ADVERSARIAL TRAINING METHODS FOR SEMI-SUPERVISED TEXT CLASSIFICATION

FGSM 介绍

EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES

对话系统

ConvLab 代码解读

DSTC8 对话评测代码框架

DialogFlow 试用

一个很好的对话机器人产品化的例子

微软小冰解读

The Design and Implementation of XiaoIce, an Empathetic Social Chatbot

聚类算法

HDBSCAN 简介

一种基于密度的聚类方法

DBSCAN 简介

一种基于密度的聚类方法

K-Means 简介

一种基于质心的聚类方法

聚类简介

知识生产和数据挖掘利器

迁移学习

SMART 介绍

Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

归因分析

浅谈归因分析和模型可解释性

探索赛事对游戏的价值分析

因果推断

浅谈归因分析和模型可解释性

探索赛事对游戏的价值分析

模型可解释性

浅谈归因分析和模型可解释性

探索赛事对游戏的价值分析