526互联

semi-supervised pseudo-label supervised efficient

[VLDB 2012]Efficient Subgraph Matching on Billion Node Graphs

[VLDB 2012]Efficient Subgraph Matching on Billion Node Graphs 重点了解实现star-join的具体过程。 分解query和STwigs排序 文中把star叫做STwigs，每一个STwigs查询为\(q=(r, L)\)，其中r是跟节点标 ......
Efficient Subgraph Matching Billion Graphs

Graph Construction and b-Matching for Semi-Supervised Learning

目录概符号说明图的构建Graph Sparsification\(\epsilon\)-neighborhood graph\(k\)NN graph\(b\)-MatchingGraph Edge Re-Weighting Jebara T., Wang J. and Chang S. Graph ......
Semi-Supervised Construction Supervised b-Matching Matching

Proj CDeepFuzz Paper Reading: SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks

## Abstract 本文：SparseProp Github: https://github.com/IST-DASLab/sparseprop Task: a back-propagation algo for sparse training data, a fast vectorized i ......
Backpropagation SparseProp CDeepFuzz Efficient Networks

论文精读：带有源标签自适应的半监督域适应（Semi-Supervised Domain Adaptation with Source Label Adaptation）

# Semi-Supervised Domain Adaptation with Source Label Adaptation 具有源标签适应的半监督域适应 >[原文链接](https://openaccess.thecvf.com/content/CVPR2023/papers/Yu_Semi- ......
Adaptation Semi-Supervised Supervised 标签 Domain

​MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression

​MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression MPDIoU:一个有效和准确的边界框损失回归函数 摘要 边界框回归(Bounding box regression, BBR)广泛应用于目标检测和实例分割，是目标定位 ......
Regression Efficient Accurate Bounding MPDIoU

[论文阅读] Learning Semi-supervised Gaussian Mixture Model

# Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discovery ## Abstract 在本文中，我们解决了广义类别发现(generalized category discovery, GCD ......
Semi-supervised supervised Learning Gaussian Mixture

Proj CDeepFuzz Paper Reading: Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation

## Abstract 背景： 1. the de facto standard to assess the quality of DNNs in the industry is to check their performance (accuracy) on a collected set of ......
Labeling-Free Estimation CDeepFuzz Efficient Accuracy

论文解读（TAMEPT）《A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification》

论文信息 论文标题：A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification论文作者：Yunlong Feng, Bohan Li, Libo Qin, Xiao Xu, ......
Self-Supervised Classification Distillation Cross-Domain Supervised

论文解读（KDSSDA）《Knowledge distillation for semi-supervised domain adaptation》

Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Knowledge distillation for semi-supervised domain adaptation论文作者：Mauricio Orbes-Arteaga, Jorge Cardoso论 ......
semi-supervised distillation adaptation supervised Knowledge

论文解读（ECACL）《ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation》

Note：[ wechat：Y466551 | 付费咨询，非诚勿扰 ] 论文信息 论文标题：ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation论文作者：Kai Li, Chang Liu, Handong Zhao, Y ......
ECACL Semi-Supervised Adaptation Supervised Framework

CLIP: Learning Transferable Visual Models From Natural Language Supervision

## CLIP: Learning Transferable Visual Models From Natural Language Supervision 论文链接： https://arxiv.org/pdf/2103.00020.pdf 代码链接：https://github.com/open ......
Transferable Supervision Learning Language Natural

[论文精读][计算生物][蛋白质预训练表示]Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy

笔者正在调研市面上的蛋白表示方法，论文方法过于数理的部分会被抽象带过。 ## Basic Information: * Title: Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein St ......
Protein Data-Efficient 蛋白质 Pretraining Refinement

Learning Transferable Visual Models From Natural Language Supervision

Learning Transferable Visual Models From Natural Language Supervision 作者：Alec Radford *1 Jong Wook Kim *1 Chris Hallacy 1 Aditya Ramesh 1 Gabriel Goh ......
Transferable Supervision Learning Language Natural

论文解读（APCA）《Adaptive prototype and consistency alignment for semi-supervised domain adaptation》

[ Wechat：Y466551 | 付费咨询，非诚勿扰 ] 论文信息 论文标题：Adaptive prototype and consistency alignment for semi-supervised domain adaptation论文作者：Jihong Ouyang、Zhengjie ......
semi-supervised consistency adaptation supervised prototype

Efficient and Accurate Diagnostic Tool

Diagnostic tools play a crucial role in the automotive industry, allowing technicians to accurately identify and troubleshoot vehicle issues. Among th ......
Diagnostic Efficient Accurate Tool and

Classical Management: emphasized rationality and making organizations and workers as efficient as possible

Classical approach: First studies of management, which emphasized: * rationality * making organizations and workers as efficient as possible **Max Web ......
organizations rationality Management emphasized Classical

GLoRA：One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning

# GLoRA：One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning ## O、Abstract 本文在 LoRA 的基础上，提出一种广义 LoRA （GLoRA，Generalized LoRA）。与 LoRA 相比，G ......
Parameter-Efficient Fine-tuning One-for-All Generalized Efficient

[AAAI 2023]Self-Supervised Bidirectional Learning for Graph Matching

# Self-Supervised Bidirectional Learning for Graph Matching ## 动机 Graph Matching（GM）是个NP难问题。随着机器学习的兴起，该问题也有望被更高效地解决。然而，现有的监督学习仍然需要为了训练去计算大量的ground tru ......
Self-Supervised Bidirectional Supervised Learning Matching

[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 ......
Self-supervised Transformers Lightweight supervised Closer

[VLDBJ 2022]Privacy and efficiency guaranteed social subgraph matching

# Privacy and efficiency guaranteed social subgraph matching ## 动机 目标是在不影响查询处理的同时保护隐私 ## 其中的子图匹配算法PGP ![img](https://img2023.cnblogs.com/blog/2988279/ ......
efficiency guaranteed matching subgraph Privacy

Efficient GPU-Accelerated Subgraph Matching

# Efficient GPU-Accelerated Subgraph Matching ## 总结 核心在利用GPU并行计算，为此设计了更适合GPU查询的数据结构，并混合BFS-DFS（先广度过滤再深度匹配）实现更好的时空复杂度 ## 动机 现有的算法都是先过滤再枚举。常规的CPU算法一次只能计 ......
GPU-Accelerated Accelerated Efficient Subgraph Matching

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

详解树莓派上如何安装Home Assistant Supervised

转载自：https://www.mintimate.cn/2022/03/29/raspberryInsatllHAS/ Home Assistant的大名，想必大家都知道，使用它可以轻易把米家的设备，桥接到Apple的HomeKit，让用户可以用Siri就可以控制小米设备。当然，我们用树莓派，不想 ......
树莓 Supervised Assistant Home

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

[TOC] > [Xia X., Yin H., Yu J., Wang Q., Cui L and Zhang X. Self-supervised hypergraph convolutional networks for session-based recommendation. AAAI, ......
Self-Supervised Recommendation Convolutional Session-based Hypergraph

Self-Supervised Graph Co-Training for Session-based Recommendation

[TOC] > [Xia X., Yin H., Yu J., Shao Y. and Cui L. Self-supervised graph co-training for session-based recommendation. CIKM, 2021.](http://arxiv.org/a ......
Self-Supervised Recommendation Session-based Co-Training Supervised

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

Efficient Correction of Single InsertionlDeletion and Multi-Substitution Errors

Efficient Correction of Single InsertionlDeletion and Multi-Substitution ErrorsG. J. Han, Y. L. Guan, K. Cai, K. S. Chan, and L. J. Kong A!JshYlc�A tw ......
InsertionlDeletion Multi-Substitution Substitution Correction Efficient

Efficient Graph Generation with Graph Recurrent Attention Networks

[TOC] > [Liao R., Li Y., Song Y., Wang S., Nash C., Hamilton W. L., Duvenaud D., Urtasun R. and Zemel R. NIPS, 2019.](http://arxiv.org/abs/1910.00760) ......
Graph Generation Efficient Attention Recurrent

CLIP-S^4：Language-Guided Self-Supervised Semantic Segmentation论文阅读笔记

## 摘要 作者提出了CLIP-S4，借助自监督像素表示学习和V-L模型实现各种语义分割任务，不需要使用任何像素级别标注以及未知类的信息。作者首先通过对图像的不同增强视角进行像素-分割对比学习来学习像素嵌入。之后，为进一步改善像素嵌入并实现基于自然语言的语义分割，作者设计了由V-L模型指导的嵌入一致 ......
Language-Guided Self-Supervised Segmentation Supervised Language

Weakly Supervised Temporal Action Localization via Representative Snippet Knowledge Propagation概述

0.前言 相关资料： arxiv github 论文解读 论文基本信息： 领域：弱监督时序动作定位 发表时间：CVPR2022(2022.3.14) 1.针对的问题 许多现有的方法试图生成伪标签来弥补分类和定位之间的差异，但通常只使用有限的上下文信息，即每个片段内的信息，来生成伪标签。 2.主要贡献 ......
Representative Localization Propagation Supervised Knowledge
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