本博客是针对周志华教授所著《机器学习》的“第11章 特征选择与稀疏学习”部分内容的学习笔记。 在实际使用机器学习算法的过程中,往往在特征选择这一块是一个比较让人模棱两可的问题,有时候可能不知道如果想要让当前的模型效果更好,到底是应该加还是减掉一些特征,加又是加哪些,减又是减哪些,所以借着对这一章内容...
Add a description, image, and links to the sparse-learning topic page so that developers can more easily learn about it. Curate this topic Add this topic to your repo To associate your repository with the sparse-learning topic, visit your repo's landing page and select "manage topics....
SPARSE LEARNING FOR COMPUTER VISIONProvided is a process that includes training a computer-vision object recognition model with a training data set including images depicting objects, each image being labeled with an object identifier of the corresponding object; obtaining a new image; determining a ...
Sparse Q-Learning 在给定最优价值函数的闭式表达式后,进一步需要实例化该算法。为了完全避免OOD动作,本文设定了一个约束:u(a|s)=0⇒\pi(a|s)=0,能够引出α-divergence,它是f-divergence的一个子集,其形式如下:其中α取值为除0,1以外的实值。当\alpha\le 0时,α-divergence呈现mode-seeking 其中当\alpha...
Install the sparse learning library:python setup.py install Basic Usage MNIST & CIFAR-10 models MNIST and CIFAR-10 code can be found in themnist_cifarsubfolder. You can runpython main.py --data DATASET_NAME --model MODEL_NAMEto run a model on MNIST (--data mnist) or CIFAR-10 (--dat...
(PCM) memristor array and quantified the unique resistance drift effect. On this basis, spontaneous sparse learning (SSL) scheme that leverages the resistance drift to improve PCM-based memristor network training is developed. During training, SSL regards the drift effect as spontaneous consistency-...
In fact, there are few works concerning distributed sparse learning in the Byzantine setup. In this paper, we propose a Byzantine-robust distributed method which can learn the sparse structure for M-estimation. We assume that XX,Y are generated from the linear model Y=XXTββ∗+ϵ. (5)...
Sparse learning and stability selection for predicting MCI to AD conversion using baseline ADNI data Jieping Ye, Michael Farnum, Eric Yang, Rudi Verbeeck, Victor Lobanov, Nandini Raghavan, Gerald Novak, Allitia DiBernardo & Vaibhav A Narayan for the Alzheimer’s Disease Neuroimaging In...
In this research a new learning algorithm called New Sparse Learning Machine (NSLM) for single-hidden layer feedforward networks is proposed for regression and classification. In the first phase, the algorithm creates hidden layer with small correlation among nodes by orthogonalizing the columns of ...
深度学习(Deep Learning)话题下的优秀答主167 人赞同了该文章 目录 收起 前言 1. 算法动机 2. 稀疏Transformer 2.1 普通自注意力 2.2 分解自注意力(Factorized Self-Attention) 2.2.1 跨步注意力 2.2.2 固定注意力 2.2.3 分解注意力头 2.3 多层Transformer训练 2.4 Gradient Checkpointing 2.5 混合精度训练...