International Journal of Machine Learning (IJML) is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of machine learning. The focus is to publish papers on state-of-the-art machine learning. Submitted papers will be reviewed by technical committees of the Journal and Association. The audience includes researchers, managers and operators for machine learning and computing as well as designers and developers.
All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing.
Abstract—Energy is essential to facilitate the social andeconomic growth of a society But this energy generation [Click]
Abstract—Under various risks, companies are required to be resilient, so that they can flexibly respond to change [Click]
Abstract—More research is being done to find out how well-being can be predicted using well-designed models To [Click]
Abstract—The project aims to boost the mental health of Australians using RASA-trained chatbots JoyBot was traine [Click]
Abstract—The objective of speech enhancement (SE) is to alleviate various types of distortion (noise, channel effe [Click]
Abstract—This paper presents an embedded deep neural network model to predict the driver rank and the optimum pi [Click]
Abstract—In this paper, we solve the bi-objective obnoxious with a population-based method The designed algorithm [Click]
Abstract—Binary neural networks (BNNs) have drawn much attention recently because they possess the most promising [Click]
Abstract—The cancellation of subscribers is always a matter of special concern for service providers in general a [Click]
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