Titlebook: Machine Learning and Other Soft Computing Techniques: Biomedical and Related Applications; Nguyen Hoang Phuong,Nguyen Thi Huyen Chau,Vladi

结构

过剩

,How to Best Retrain a Neural Network if We Added One More Input Variable,re-training will take a lot of time, almost as much as the original training. In this paper, we show, both theoretically and experimentally, that in such situations, we can speed up re-training—practically without decreasing resulting accuracy—if we only update some weights.

乞丐

凹室

POWER

,Why Bump Reward Function Works Well in Training Insulin Delivery Systems,situations and regulate blood glucose level, patients with severe form of diabetes need insulin injections. Ideally, the system should automatically decide when best to inject insulin and how much to inject. To find the optimal control, researchers applied machine learning with different reward func

accrete

思想灵活

,How to Best Retrain a Neural Network if We Added One More Input Variable,values of an additional quantity that have some influence on .. In such situations, it is desirable to re-train the neural network, so that it will be able to take this extra value into account. A straightforward idea is to add a new input to the first layer and to update all the weights based on th

Interferons

,Towards a Psychologically Natural Relation Between Colors and Fuzzy Degrees,ium: light. Light consists of components of different color. So, if we use optical color computations to process fuzzy data, we need to associate fuzzy degrees with colors. One of the main features—and of the main advantages—of fuzzy technique is that the corresponding data has intuitive natural mea

opportune

ASSET