recommendations distributions lightweight confidence

[VLDBJ 2019]Distributed Subgraph Matching on Timely Dataflow

# [VLDBJ 2019]Distributed Subgraph Matching on Timely Dataflow **只关注这篇中的subgraph matching的内容** ## 定义 $g = (V_g, E_g, L_g)$分别表示点、边,以及把任意点或边映射成label的函数。 ......

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

[TOC] > [Fan Z., Liu Z., Zhang J., Xiong Y., Zheng L. and Yu P. S. Continuous-time sequential recommendation with temporal graph collaborative transfo ......

大模型时代的推荐系统Recommender Systems in the Era of Large Language Models (LLMs)

文章地址:https://arxiv.org/abs/2307.02046 笔记中的一些小实验中的模型都是基于GPT-3.5架构的ChatGPT模型。 本文主要讲述了比较具有代表性的方法利用LLM去学习user和item的表示,从预训练、微调和提示三个范式回顾了近期用于增强推荐系统的LLM先进技术, ......
Recommender Language 模型 Systems 时代

Position-Enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations

# Position-Enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations [TOC] > [Huang L., Ma Y., Liu Y., Du B., Wang S. and Li ......

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

长尾问题是个老大难问题了。 在推荐中可以是用户/物料冷启动,在搜索中可以是中低频query、文档,在分类问题中可以是类别不均衡。长尾数据就像机器学习领域的一朵乌云,飘到哪哪里就阴暗一片。今天就介绍来自Google的一篇解决长尾物品推荐的论文。 ......

Time-aware Path Reasoning on Knowledge Graph for Recommendation

[TOC] > [Zhao Y., Wang X., Chen J., Wang Y., Tang W., He X. and Xie H. Time-aware path reasoning on knowledge graph for recommendation. TOIS, 2022.](h ......

How Can Recommender Systems Benefit from Large Language Models: A Survey 阅读笔记

论文主要从LLM应用在推荐系统哪些部分以及LLM如何应用在推荐系统中,还讨论了目前LLM应用在RS中的一些问题。 ###Where? 推荐系统哪些部分哪里可以应用到大模型?文章中提到了特征工程、特征编码、评分/排序函数、推荐流程控制。 - LLM for Feature Engineering - ......
Recommender Language Benefit Systems 笔记

【CF1348C】Phoenix and Distribution(构造、贪心)

**题目大意:** 将给定的$n(1\le n\le10^{5})$个字符分配为$k$个字符串(不能有空串),求此操作得到的字典序最大的字符串最小的情况。 我们先将给定的字符按照字典序从小到大排序,然后逐个分配给字符串。我们要让字典序最大的字符串尽可能小,所以将第$i$个字符安排在第$i$字符串的头 ......
Distribution Phoenix 1348C 1348 and

UVA12390 Distributing Ballot Boxes 题解

[题目传送门](https://www.luogu.com.cn/problem/UVA12390) ## 题意 有 $n$ 个城市,$b$ 个投票箱,第 $i$ 个城市有 $a_i$ 人,每个人均有一张票,将 $b$ 个投票箱分给 $n$ 个城市,每个城市的票分摊在投票箱里,求所有城市中最多的投票 ......
题解 Distributing Ballot 12390 Boxes

A Neural Influence Diffusion Model for Social Recommendation

[TOC] > [Wu L., Sun P., Fu Y., Hong R., Wang X. and Wang M. A neural influence diffusion model for social recommendation. SIGIR, 2019.](https://dl.acm ......

SocialLGN Light graph convolution network for social recommendation

[TOC] > [Liao J., Zhou W., Luo F., Wen J., Gao M., Li X. and Zeng J. SocialLGN: Light graph convolution network for social recommendation. Information ......

Distributions: Uniform | Cauchy |

Uniform Distribution: U(a, b): * F(x) = x ·1/(b-a) * p(x) = 1/(b-a) if q<x<b; p(x) = 0 else. * E(x) = (a+b)/2 Cauchy Distribution: * F(x) = [arctan(x) ......
Distributions Uniform Cauchy

论文解读(SimGCL)《Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation》

Note:[ wechat:Y466551 | 可加勿骚扰,付费咨询 ] 论文信息 论文标题:Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation论文作者:Junliang Yu ......

hive 的order by ,sort by,distribute by,cluster by

order by order by会对输入做全局排序,因此只有一个Reducer(多个Reducer无法保证全局有序),然而只有一个Reducer,会导致当输入规模较大时,消耗较长的计算时间,在生产环境中遇到数据量较大的情况,一般无法成功。 sort by sort by不是全局排序,其在数据进入r ......
distribute cluster order hive by

论文解读(LightGCL)《LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation》

Note:[ wechat:Y466551 | 可加勿骚扰,付费咨询 ] 论文信息 论文标题:LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation论文作者:Cai, Xuheng and Huang, ......

HS-GCN Hamming Spatial Graph Convolutional Networks for Recommendation

[TOC] > [Liu H., Wei Y., Yin J. and Nie L. HS-GCN: Hamming spatial graph convolutional networks for recommendation. IEEE TKDE.](https://arxiv.org/pdf/ ......

[论文阅读笔记] AnoShift - A Distribution Shift Benchmark for U

# AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection 主要贡献点: 1. 用t-SNE,Optimal Transport Dataset Distance 分析了网络流量中用于无监督异常检测任务的 ......

Improved deep reinforcement learning for robotics through distribution-based experience retention

![](https://img2023.cnblogs.com/blog/1428973/202307/1428973-20230729080850680-1663030080.png) **发表时间:**2016(IROS 2016) **文章要点:**这篇文章提出了experience repl ......

Proj. CMI Paper Reading: Distributed System Fuzzing

## Abstract 背景:当前分布式系统分析一般都是黑盒工具,难以探索程序状态 工具:MALLORY 任务:greybox fuzzing testing distributed system 方法:timeline-driven testing, timeline abstraction 步骤 ......
Distributed Fuzzing Reading System Paper

Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning

图的作用: 图结构捕捉不同类型节点(即用户、项目和属性)之间丰富的关联信息,使我们能够发现协作用户对属性和项目的偏好。因此,我们可以利用图结构将推荐和对话组件有机地整合在一起,其中对话会话可以被视为在图中维护的节点序列,以动态地利用对话历史来预测下一轮的行动。 由四个主要组件组成:基于图的 MDP ......

粗读Multi-Task Recommendations with Reinforcement Learning

论文: Multi-Task Recommendations with Reinforcement Learning 地址: https://arxiv.org/abs/2302.03328 # 摘要 In recent years, Multi-task Learning (MTL) has yi ......

6.5840: Distributed Systems

# 相关信息 课程链接: https://pdos.csail.mit.edu/6.824/schedule.html Next Step: - 7.18 LEC 2 - 7.17 MapReduce paper, LEC 2 Preparation - 7.16 MapReduce video # ......
Distributed Systems 6.5840 5840

[论文速览] A Closer Look at Self-supervised Lightweight Vision Transformers

## Pre title: A Closer Look at Self-supervised Lightweight Vision Transformers accepted: ICML 2023 paper: https://arxiv.org/abs/2205.14443 code: https ......

MEANTIME Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation

[TOC] > [Cho S., Park E. and Yoo S. MEANTIME: Mixture of attention mechanisms with multi-temporal embeddings for sequential recommendation. RecSys, 20 ......

[SIGMOD 2022]Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process

# Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process ## 总结 用无限宽度神经网络和高斯过程来等价贝叶斯过程,并利用主动学习提高精度,实现对某个SQL查询的cost估算 ## 动机 ......

GMI Distribution EDI 需求详解

GMI Distribution 是一家在全球范围内运营的企业,专注于货物分销和供应链管理。作为一家创立于数十年前的公司,GMI Distribution 已经取得了卓越的成就和荣誉。GMI 的目标是提供高效、可靠的供应链解决方案,帮助客户实现业务增长并提升竞争力。凭借多年来积累的经验和专业知识,在 ......
Distribution 需求 GMI EDI

Memory Augmented Graph Neural Networks for Sequential Recommendation

[TOC] > [Ma C., Ma L., Zhang Y., Sun J., Liu X. and Coates M. Memory augmented graph neural networks for sequential recommendation. AAAI, 2021.](http: ......

iOS distribution发布证书过期或者被手动revoke了app会被下架吗?

​ 在距离distribution 证书过期一个月(或被手动revoke了)的时候会受到apple的邮件 ​编辑 虽然distribution过期(或者被手动revoke)了,如果你的开发者账号是company(公司)类型或个人类型的,只要你的每年99$的开发者membership没有过期,就不会对 ......
distribution 手动 证书 revoke iOS

在距离distribution 证书过期一个月(或被手动revoke了)的时候会受到apple的邮件

​ ​编辑 虽然distribution过期(或者被手动revoke)了,如果你的开发者账号是company(公司)类型或个人类型的,只要你的每年99$的开发者membership没有过期,就不会对已上架的app产生影响,只是你下次发布或者更新app就要重新生成一个distribution证书了。如 ......
distribution 手动 证书 邮件 时候

关于Deep Neural Networks for YouTube Recommendations的一些思考和实现

作者自己实现该文章的时候遇到的一些值得思考的地方: - [关于Deep Neural Networks for YouTube Recommendations的一些思考和实现](https://cloud.tencent.com/developer/article/1170340) - [备份网址] ......
Recommendations Networks YouTube Neural Deep