http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Semi-Supervised Learning for Stratified Networks
Myungjun Kim(김명준),Yonghyun Nam(남용현),Sangkuk Lee(이상국),Hyunjung Shin(신현정) 한국경영과학회 2016 한국경영과학회 학술대회논문집 Vol.2016 No.4
This research is concerned with developing a semi-supervised learning algorithm for stratified networks. In stratified networks, labels in one stratum can benefit predictions in other strata through inter-stratum connections so dealing with inter-stratum connections is important. Technically, the problem of non-squareness and sparseness involved in matrix inversion for interstratum connections must be solved. In order to verify the validity of the algorithm, it was applied on disease-symptom network structure to predict cooccurrence of two diseases.
Semi-Supervised Learning for Stratified Networks
Myungjun Kim(김명준),Yonghyun Nam(남용현),Sangkuk Lee(이상국),Hyunjung Shin(신현정) 대한산업공학회 2016 대한산업공학회 춘계학술대회논문집 Vol.2016 No.4
This research is concerned with developing a semi-supervised learning algorithm for stratified networks. In stratified networks, labels in one stratum can benefit predictions in other strata through inter-stratum connections so dealing with inter-stratum connections is important. Technically, the problem of non-squareness and sparseness involved in matrix inversion for interstratum connections must be solved. In order to verify the validity of the algorithm, it was applied on disease-symptom network structure to predict cooccurrence of two diseases.