526互联

semi-supervised pseudo-label supervised efficient

SHARPNESS-AWARE MINIMIZATION FOR EFFICIENTLY IMPROVING GENERALIZATION论文阅读笔记

Intro 在训练集上最小化损失很可能导致泛化性低，因为当今模型的过参数化会导致training loss的landscape异常复杂且非凸，包含很多local/global minima，因此优化器的选择至关重要。loss landscape的几何性质（特别是minima的flatness）与泛化 ......
SHARPNESS-AWARE GENERALIZATION MINIMIZATION EFFICIENTLY SHARPNESS

Early lameness detection in dairy cattle based on wearable gait analysis using semi-supervised LSTM-Autoencoder

一区top Computers and Electronics in Agriculture 题目：“基于半监督 LSTM-自动编码器可穿戴步态分析的奶牛早期跛行检测” (Zhang 等, 2023, p. 1) (pdf) “Early lameness detection in dairy ca ......
LSTM-Autoencoder semi-supervised Autoencoder supervised detection

Supervised Machine Learning : Regression and Classification

The course is available at : Supervised Machine Learning: Regression and Classification - Week 1: Introduction to Machine Learning - Week 1 | Coursera ......
Classification Supervised Regression Learning Machine

LocPatcH An efficient long-read hybrid error correction algorithm based on local pHMM

该文档主要介绍了一种基于装配的方法和概率隐藏马尔科夫模型 (pHMM) 用于纠正长读序列的错误。文档详细描述了对酵母数据进行实验的结果、纠正方法的拓扑结构以及实验设置和数据集。 这种基于装配的纠正方法相对于直接纠正存在哪些优势？ pHMM 的拓扑结构是怎样的？ 在实验中使用了什么样的数据集？ 提示： ......
correction efficient algorithm long-read LocPatcH

论文阅读-Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks

1. GARF 简介 代码地址：https://github.com/PJinfeng/Garf-master 基于 SeqGAN 提出了一种自监督、数据驱动的数据清洗框架——GARF。 GARF 的数据清洗分为两个步骤： 规则生成 (Rule generation with SeqGAN)：利用 ......
Self-supervised Interpretable Adversarial Generative supervised

《Learning Transferable Visual Models From Natural Language Supervision》论文学习

一、Abstract 最先进的计算机视觉系统被训练用以预测一组预定的固定目标类别。这种受限的监督方式限制了它们的通用性和可用性，因为需要额外的标记数据来指定任何新的视觉概念。因此，直接从关于图像的原始描述文本中学习是一个有希望的替代方法，它利用了更广泛的因特网监督来源。 我们证明了预测哪个标题与哪张 ......
Transferable Supervision Learning Language Natural

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery * Authors: [[Libo Wang]], [[Rui Li]], [[ ......
segmentation transformer UNetFormer UNet-like efficient

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network * Authors: [[Wenzhe Shi]], [[Jose Caballer ......
Super-Resolution Convolutional Resolution Real-Time Efficient

High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation

目录简介创新点内容Entropy Coding Using Multistage Context Model模型结构残差邻域注意力块Residual Neighborhood Attention Block RNAB激活函数 高斯误差线性单元激活函数GELU并行解码 简介 创新点 Integrate ......
High-Efficiency Neighborhood Aggregation Information Efficiency

[论文速览] Randomized Quantization@ A Generic Augmentation for Data Agnostic Self-supervised Learning

Pre title: Randomized Quantization: A Generic Augmentation for Data Agnostic Self-supervised Learning accepted: ICCV 2023 paper: https://arxiv.org/abs ......
Self-supervised Quantization Augmentation Randomized supervised

CA-TCC: 半监督时间序列分类的自监督对比表征学习《Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification》(时间序列、时序表征、时间和上下文对比、对比学习、自监督学习、半监督学习、TS-TCC的扩展版)

现在是2023年11月27日，10:48，今天把这篇论文看了。 论文：Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification GitHub：https://g ......
时间序列 时间 序列 supervised 时序

【HFSS】仿真时radiation efficiency（辐射效率）大于1

![image](https://img2023.cnblogs.com/blog/2603751/202311/2603751-20231121124817927-404911195.png) ![image](https://img2023.cnblogs.com/blog/2603751/20... ......
efficiency radiation 效率 HFSS

什么是人工智能领域的 SFT - Supervised Finetuning

在人工智能（AI）领域，Supervised Finetuning 是一个重要的概念。它涉及到在预训练模型的基础上，利用有标签的数据进行微调，以适应特定的任务或领域。这个过程可以被视为在更广泛的知识基础上进行特定任务的训练，从而在新任务上获得更好的性能。 Supervised Finetuning ......
人工智能 Finetuning Supervised 人工 领域

基于时间频率一致性对时间序列进行自监督对比预训练《Self-Supervised Contrastive Pre-Training for Time Series via Time-Frequency Consistency》(时序、时频一致性、对比学习)

2023年11月10日，今天看一篇论文，现在17:34，说实话，想摆烂休息，不想看，可还是要看，拴Q。 论文：Self-Supervised Contrastive Pre-Training for Time Series via Time-Frequency Consistency 或者是：Sel ......
一致性 时间序列 时间 时序 Time

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation

目录概TallRec代码 Bao K., Zhang J., Zhang Y., Wang W., Feng F. and He X. TALLRec: An effective and efficient tuning framework to align large language model ......
Recommendation Effective Efficient Framework Language

2023CVPR_Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring

一. Motivation 1. Transformer在解决全局表现很好，但是复杂度很高，主要体现在QK的乘积: (We note that the scaled dot-product attention computation is actually to estimate the corre ......
CVPR_Efficient Domain-based Transformers High-Quality Deblurring

Checkerboard Context Model for Efficient Learned Image Compression

目录AbstractIntroductionPreliminary 初步介绍Variational Image Compression with Hyperprior(超先验变分图像压缩)Autoregressive Context(自回归上下文模型)Parallel Context Modelin ......
Checkerboard Compression Efficient Context Learned

ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

abstruct \(\quad\) 受能量压缩表现的启发，提出了不均匀通道情况自适应编码.结合不均匀分组模型和现有上下文模型，获得一种空间通道上下文自适应模型，来提高编码性能，而不影响其运行时间。 \(\quad\)这种模型支持预览解码和渐进解码。 introduction 学习图像压缩中最重要的 ......
Space-Channel Compression Contextual Efficient Adaptive

【CVPR2023】Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

> 论文：https://readpaper.com/paper/4728855966703960065 代码：https://github.com/ofsoundof/GRL-Image-Restoration 这个论文的代码地址叫GRL，意思是 Global, Regional, Local 的 ......
Image Hierarchies Restoration Efficient Modelling

2023ACMMM_Mutual Information-driven Triple Interaction Network for Efficient Image Dehazing

一. Motivation 之前网络存在的缺点： 1. 使用的有限的频域信息 2. 不充足的信息交互 ： (1) 第一阶段的输出直接作为第二阶段的输入，忽略了中间特征从早期到后期的传播 (2) 在编码器解码器结构同尺度之间进行特征融合，忽略了阶段内和跨阶段的跨尺度信息交换 3. 严重的特征冗余：中间 ......
Information-driven ACMMM_Mutual Information Interaction Efficient

ST-SSL: 用于交通流量预测的时空自监督学习《Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction》(交通流量预测、自监督)

2023年10月23日，继续论文，好困，想发疯。 论文：Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction Github：https://github.com/Echo-Ji/ST-SSL AAAI 2023的论文 ......
流量 交通 Spatio-Temporal Self-Supervised Prediction

【PRC】鲁棒跨域伪标记和对比学习的无监督域自适应NIR-VIS人脸识别 Robust Cross-Domain Pseudo-Labeling and Contrastive Learning for Unsupervised Domain Adaptation NIR-VIS Face Recognition

【该文章为杨学长的文章，膜拜】 探索跨领域数据中的内在关系并学习领域不变表示 由于需要在低光照条件下实现24h的人脸识别，近红外加可见光的(NIR-VIS)人脸识别受到了更多的关注。但是数据标注是一个难点。该文章提出了Robust crossdomain Pseudo-labeling and Co ......
NIR-VIS Domain 人脸 Pseudo-Labeling Cross-Domain

Graph Laplacian for Semi-Supervised Learning

目录概符号说明Graph-Laplacian for SSL Streicher O. and Gilboa G. Graph laplacian for semi-supervised learning. arXiv preprint arXiv:2301.04956, 2023. 概 标题取得有 ......
Semi-Supervised Supervised Laplacian Learning Graph

Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning论文阅读

2023 ICCV Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning论文阅读，思想很妙，该笔记非常简要 ......
Self-Supervised Representation Autoencoder Point-Cloud Supervised

论文阅读：A Lightweight Knowledge Graph Embedding Framework for Efficient Inference and Storage

ABSTRACT 现存的KGE方法无法适用于大规模的图（由于存储和推理效率的限制） 作者提出了一种LightKG框架： 自动的推断出码本codebooks和码字codewords，为每个实体生成合适的embedding。 同时，框架中包含残差模块来实现码本的多样性，并且包含连续函数来近似的实现码字的 ......
Lightweight Knowledge Embedding Efficient Framework

G7、Semi-Supervised GAN 理论与实战

🍨 本文为🔗365天深度学习训练营 中的学习记录博客 🍖 原作者：K同学啊 🚀 文章来源：K同学的学习圈子 问题由来¶ 如果我们生成的图像是带有标签的，例如数字0-9，那为什么要鉴别器判断输入图像为真假，而不直接判断图像是0-9中的哪一个数字呢，这样的鉴别效果不是更好吗 一、SGAN理论基础 ......
Semi-Supervised Supervised 实战 理论 Semi

论文解读（CR-Match）《Revisiting Consistency Regularization for Semi-Supervised Learning》

Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Revisiting Consistency Regularization for Semi-Supervised Learning论文作者：Yue Fan、Anna Kukleva、Bernt Schie ......
Semi-Supervised Regularization Consistency Revisiting Supervised

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables

郑重声明：原文参见标题，如有侵权，请联系作者，将会撤销发布！ Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5331-5340, 2019 ......
Meta-Reinforcement Reinforcement Probabilistic Off-Policy Efficient

论文解读（FixMatch）《FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence》

Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence论文作者：论文来源：2020 aRxiv论文地址： ......
FixMatch Semi-Supervised Consistency Simplifying Confidence

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models 阅读笔记（11.2） 摘要：优化MSE指标通常会导致模糊，特别是在高方差(详细)区域。我们提出了一种基于创建正确降尺度的 ......
Self-Supervised Exploration Generative Supervised Upsampling
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