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A Brief Introduction To Weakly Supervised Learning. Typically there are three types of weak supervision. Inexact supervision where the training data are given with only coarse-grained labels. In Weakly Supervised Learning WSL use cases eg. And inaccurate supervision where the given labels are not always ground-truth.
Weakly supervised learning is an umbrella covering a va-riety of studies which attempt to construct predictive mod-els by learning with weak supervision. Supervised learning techniques construct predictive models by learning from a large number of training examples where each training example has a label indicating its ground-truth output. 南京大学周志华教授在2018年1月发表了一篇论文叫做A Brief Introduction to Weakly Supervised Learning对机器学习任务给出了一个新的趋势和思路. Inexact supervision where the training data are given with only coarse-grained labels. Regression is a predictive statistical process where the model attempts to find the important relationship. Incomplete supervision where only a subset of training data is given with labels.
摘要 Supervised learning techniques construct predictive models by learning from a large number of training examples where each training example has a label indicating its ground-truth output.
Though current techniques have achieved great success. Inexact supervision where the training data are given with only coarse-grained labels. Bootstrapping also called self-training is a form of learning that is designed to use even less training examples therefore sometimes called weakly-supervised. 南京大学周志华教授在2018年1月发表了一篇论文叫做A Brief Introduction to Weakly Supervised Learning对机器学习任务给出了一个新的趋势和思路. Weakly supervised learning is an umbrella covering a va-riety of studies which attempt to construct predictive mod-els by learning with weak supervision. A Brief Introduction to Weakly Supervised Learning.