Search Results for author: Hong Zhao

Found 13 papers, 1 papers with code

How and what to learn:The modes of machine learning

no code implementations28 Feb 2022 Sihan Feng, Yong Zhang, Fuming Wang, Hong Zhao

It is further discovered that the key strategy to improve the performance of a neural network is to control the ratio of the two learning modes to match that of the linear and the nonlinear features, and that increasing the width or the depth of a neural network helps this ratio controlling process.

Inferring Global Dynamics Using a Learning Machine

no code implementations28 Sep 2020 Hong Zhao

It is found that following an appropriate training strategy that monotonously decreases the cost function, the learning machine in different training stage can mimic the system at different parameter set.

Time Series

Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia

no code implementations21 Feb 2020 Xiaowei Xu, Xiangao Jiang, Chunlian Ma, Peng Du, Xukun Li, Shuangzhi Lv, Liang Yu, Yanfei Chen, Junwei Su, Guanjing Lang, Yongtao Li, Hong Zhao, Kaijin Xu, Lingxiang Ruan, Wei Wu

We found that the real time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab has a relatively low positive rate in the early stage to determine COVID-19 (named by the World Health Organization).

Computed Tomography (CT) COVID-19 Diagnosis

Inferring Global Dynamics of a Black-Box System Using Machine Learning

no code implementations10 May 2019 Hong Zhao

We present that, instead of establishing the equations of motion, one can model-freely reveal the dynamical properties of a black-box system using a learning machine.

Time Series

Copy the dynamics using a learning machine

no code implementations24 Jul 2017 Hong Zhao

Trained by a set of input-output responses or a segment of time series of a black system, a learning machine can be served as a copy system to mimic the dynamics of various black systems.

Time Series

A General Theory for Training Learning Machine

no code implementations23 Apr 2017 Hong Zhao

The principle of learning, the role of the a prior knowledge, the role of neuron bias, and the basis for choosing neural transfer function and cost function, etc., are still far from clear.

Image Fusion With Cosparse Analysis Operator

no code implementations18 Apr 2017 Rui Gao, Sergiy A. Vorobyov, Hong Zhao

In our approach, we formulate the multi-focus image fusion problem in terms of an analysis sparse model, and simultaneously perform the restoration and fusion of multi-focus images.

Operator learning

General Vector Machine

no code implementations12 Feb 2016 Hong Zhao

The support vector machine (SVM) is an important class of learning machines for function approach, pattern recognition, and time-serious prediction, etc.

Rough matroids based on coverings

no code implementations2 Nov 2013 Bin Yang, Hong Zhao, William Zhu

First, we investigate some properties of the definable sets with respect to a covering.

Combinatorial Optimization

Cost-Sensitive Feature Selection of Data with Errors

no code implementations13 Dec 2012 Hong Zhao, Fan Min, William Zhu

In this paper, we study the cost-sensitive feature selection problem on numerical data with measurement errors, test costs and misclassification costs.

Minimal cost feature selection of data with normal distribution measurement errors

no code implementations12 Nov 2012 Hong Zhao, Fan Min, William Zhu

In this paper, we consider numerical data with measurement errors and study minimal cost feature selection in this model.

Test-cost-sensitive attribute reduction of data with normal distribution measurement errors

no code implementations29 Sep 2012 Hong Zhao, Fan Min, William Zhu

In this paper, we introduce normal distribution measurement errors to covering-based rough set model, and deal with test-cost-sensitive attribute reduction problem in this new model.

Decision Making

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