526互联

cross-domain sentiment analysis learning

Supervised Machine Learning Regression and Classification - Week 1

# 1. 机器学习定义 > Field of study that gives computers the ability to learn without being explicitly programmed. -- Arthur Samuel(1959) ![](https://img2023 ......
Classification Supervised Regression Learning Machine

English Learning Articles 2023-06-08 Multiple insomnia symptoms raise stroke risk in people under 50, study says

Multiple insomnia symptoms raise stroke risk in people under 50, study says If you have trouble falling asleep or staying asleep, wake up too early mo ......
Articles Learning Multiple insomnia symptoms

English Learning Articles 2023-06-07 Nonsurgical cat contraception could help curb overpopulation, study says

Nonsurgical cat contraception could help curb overpopulation, study says There are an estimated 600 million domestic cats in the world, and 80% of the ......
overpopulation contraception Nonsurgical Articles Learning

nature-deep learning

Title：Deep learning Authors：Yann LeCun Yoshua Bengio & Geoffrey Hinton doi:10.1038/nature14539 # 1. 概述 使用多处理层学习数据不同层次的抽象表示，在语音识别、视觉识别、目标检测，以及药物发明、基因学等 ......
nature-deep learning nature deep

2.3类神经网路训练不起来怎么办 (三):自动调整学习速率 (Learning Rate)

# 1. 自适应学习率调整(Adaptive Learning Rate) ## 1.1 为什么需要调整学习率 首先认识一个现象.Training stuck ≠ Small Gradient 训练卡住的原因不一定是因为 gradient 太小,即critical point，也有可能是因为振荡. ......
速率 网路 Learning 神经 怎么办

Learning to Pre-train Graph Neural Networks 学习如何预训练GNN

![image](https://img2023.cnblogs.com/blog/2992171/202306/2992171-20230607143536765-414002095.png) ![image](https://img2023.cnblogs.com/blog/2992171/20 ......
Pre-train Learning Networks Neural Graph

gdb_learn

# GDB ## 基本gdb命令 ### 运行有关命令 ```shell run（简写r）： 运行程序，当遇到断点后，程序会在断点处停止运行，等待用户输入下一步的命令。 continue（简写c）：继续执行，到下一个断点处（或运行结束） next（简写n）： 单步跟踪程序，当遇到函数调用时，直接调用 ......
gdb_learn learn gdb

Reward Modelling（RM）and Reinforcement Learning from Human Feedback（RLHF）for Large language models（LLM）技术初探

Reward Modelling（RM）and Reinforcement Learning from Human Feedback（RLHF）for Large language models（LLM）技术初探 ......
Reinforcement Modelling Learning Feedback language

Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation

[TOC] > [Qiu R., Huang Z., Ying H. and Wang Z. Contrastive learning for representation degeneration problem in sequential recommendation. WSDM, 2022.] ......
Representation Recommendation Degeneration Contrastive Sequential

Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning论文阅读笔记

## 摘要 连续学习过程中的稳定性-可塑性权衡是一个重要的问题。作者提出了Auxiliary Network Continual Learning (ANCL)，通过auxiliary network提高了模型的可塑性。 ## 方法 ### The Formulation of Auxiliary ......
Stability-Plasticity Plasticity Achieving Auxiliary Stability

火山引擎DataLeap的Catalog系统搜索实践（三）：Learning to rank与后续工作

Learning to rank Learning to rank主要分为数据收集，离线训练和在线预测三个部分。搜索系统是一个Data-driven system，因此火山引擎DataLeap的Catalog系统设计之初就需要考虑数据收集。收集的数据可以用来评估和提升搜索的效果。数据收集和在线预测前 ......
火山 DataLeap Learning Catalog 引擎

Reinforcement Learning之Q-Learning - Python实现

- **算法特征** ①. 以真实reward训练Q-function; ②. 从最大Q方向更新policy $\pi$ - **算法推导** **Part Ⅰ: RL之原理** 整体交互流程如下, 定义策略函数(policy)$\pi$, 输入为状态(state)$s$, 输出为动作(action ......
Learning Reinforcement Q-Learning Python

WebSocket-Learning-1

#### WebSocket ##### 1.什么是WebSocket >> WebSocket 是一种通讯协议，目标就是替代XmlHttpRequest 和长期轮询的解决方案。应用在实时弹幕、消息推送、棋牌游戏、聊天等需要及时通讯的场景。 ##### 2.WebSocket 连接有两个阶段 >>握 ......
WebSocket-Learning WebSocket Learning

强化学习基础篇[2]：SARSA、Q-learning算法简介、应用举例、优缺点分析

# 强化学习基础篇[2]：SARSA、Q-learning算法简介、应用举例、优缺点分析 # 1.SARSA SARSA（State-Action-Reward-State-Action）是一个学习马尔可夫决策过程策略的算法，通常应用于机器学习和强化学习学习领域中。它由Rummery 和 Niran ......
优缺点 算法 Q-learning learning 基础

Machine Learning 【note_02】

# note_02 Keywords: Classification, Logistic Regression, Overfitting, Regularization ## 1 Motivation Classification: - "binary classification": $y$ ca ......
Learning Machine note 02

Machine Learning 【note_01】

Declaration (2023/06/02): This note is the first note of a series of machine learning notes. At present, the main learning resource is *the 2022 Andre ......
Learning Machine note 01

论文阅读 | Learn from Others and Be Yourself in Heterogeneous Federated Learning

**在异构联邦学习中博采众长做自己** 代码：https://paperswithcode.com/paper/learn-from-others-and-be-yourself-in **摘要** 联邦学习中有异质性问题和灾难性遗忘。首先，由于非I.I.D（相同独立分布）数据和异构体系结构，模型在 ......
Heterogeneous Federated Learning Yourself Others

April 2023-Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation

本文基于深度q网络算法提出了记忆高效的强化学习算法来缓解这一问题。通过将目标q网络中的知识整合Knowledge Consolidation到当前q网络中，所提算法减少了遗忘并保持了较高的样本效率。 ......
Memory-efficient Consolidation Reinforcement Value-based Knowledge

零样本学习（Zero-shot Learning）

零样本学习是一种机器学习的问题设置，其中模型可以对从未在训练过程中见过的类别的样本进行分类，使用一些形式的辅助信息来关联已见和未见的类别。例如，一个模型可以根据动物的文本描述来识别动物，即使它从未见过那些动物的图像。 实现零样本学习有不同的方法，取决于辅助信息的类型和学习方法。以下是一些例子： 一种 ......
样本 Zero-shot Learning Zero shot

The Importance of Particle Size Analysis in Preformulation Studies

Preformulation research is a vital link in drug development, directly affecting the subsequent development process and final application of drugs. ......
Preformulation Importance Analysis Particle Studies

事件抽取论文综述-A Survey on Deep Learning Event Extraction: Approaches and Applications

A Survey on Deep Learning Event Extraction: Approaches and Applications 1）发表信息： https://arxiv.org/abs/2107.02126 Qian Li, Jianxin Li, Member, IEEE, Ji ......
Applications Approaches Extraction Learning 事件

[论文速览] MAGE@MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

## Pre title: MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis accepted: CVPR2023 paper: https://arxiv.org/abs/221 ......
Representation Generative Synthesis Learning Encoder

Elasticsearch8.4.3安装最新ik分词器elasticsearch-analysis-ik【v8.4.3版本】

Elasticsearch8.4.3安装最新ik分词器elasticsearch-analysis-ik【v8.4.3版本】 https://blog.csdn.net/u014282578/article/details/127815352 ......
elasticsearch-analysis-ik Elasticsearch8 Elasticsearch elasticsearch 4.3

[论文阅读] Few-shot Font Generation by Learning Style Difference and Similarity

## Pre title: Few-shot Font Generation by Learning Style Difference and Similarity accepted: Arxiv 2023 paper: https://arxiv.org/abs/2301.10008 code: ......
Difference Generation Similarity Few-shot Learning

[论文速览] RectifiedFlow@Flow Straight and Fast{colon}Learning to Generate and Transfer Data with Rectified Flow

## Pre title: Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow accepted: ICLR 2023 paper: https://arxiv.org/abs/2209 ......
Flow RectifiedFlow Rectified and Learning

2023CVPR_Learning a Simple Low-light Image Enhancer from Paired Low-light Instances(PairLLE)无监督

一. motivation 以前的大多数LIE算法使用单个输入图像和几个手工制作的先验来调整照明。然而，由于单幅图像信息有限，手工先验的适应性较差，这些解决方案往往无法揭示图像细节。 二. contribution 1. 提出一个成对低光图像输入（相同内容，不同的曝光度） 2. 在输入之前进行了一个 ......
Low-light light CVPR_Learning Instances Low

learn c++ 函数返回

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函数 learn

The Difficulty of Passive Learning in Deep Reinforcement Learning

![](https://img2023.cnblogs.com/blog/1428973/202305/1428973-20230524224808789-13684847.png) **发表时间：**2021(NeurIPS 2021) **文章要点：**这篇文章提出一个tandem learni ......
Learning Reinforcement Difficulty Passive Deep

learn c++ 参数引用

#include <iostream> struct Role { int hp; int mp; int damage; }; bool Act(Role& Acter,Role& beAct) { beAct.hp -= Acter.damage; return beAct.hp < 0; } ......
参数 learn

Learning with Local and Global Consistency

[TOC] > [Zhou D., Bousquet O., Lal T. N., Weston J. and Scholk\ddot{o}pf B. Learning with local and global consistency. NIPS, 2003.](https://proceedin ......
Consistency Learning Global Local with
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