Archives

  • International AL, ML Journal Volume: 3 Issue: 9

    Vol. 3 No. 9 (2022)

    Welcome to Issue 9 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • International AL, ML Journal Volume: 2 Issue: 10

    Vol. 2 No. 10 (2013)

    Welcome to Issue 10 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • International AL, ML Journal Volume:1Issue:3

    Vol. 1 No. 3 (2020)

    Welcome to Issue 3 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • International AL, ML Journal Volume: 1 Issue: 2

    Vol. 1 No. 2 (2020)

    Welcome to Issue 2 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • International AL, ML Journal Volume: 2 Issue: 3

    Vol. 2 No. 3 (2021)

    Welcome to Issue 3 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • International AL, ML Journal Volume: 1 Issue: 2

    Vol. 1 No. 2 (2012)

    Welcome to Issue 2 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.

  • Federated Learning

    Vol. 1 No. 2 (2020)

    Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred to as clients) collaboratively train a model while ensuring that their data remains decentralized.[1] This stands in contrast to machine learning settings in which data is centrally stored. One of the primary defining characteristics of federated learning is data heterogeneity. Due to the decentralized nature of the clients' data, there is no guarantee that data samples held by each client are independently and identically distributed.

    Federated learning is generally concerned with and motivated by issues such as data privacy, data minimization, and data access rights. Its applications involve a variety of research areas including defense, telecommunications, the Internet of Things, and pharmaceuticals.

  • International AL, ML Journal Volume: 1 Issue: 3

    Vol. 1 No. 3 (2020)

    Welcome to Issue 3 of the Journal of Artificial Intelligence and Machine Learning, where we delve into groundbreaking research and pioneering advancements in the field. This issue brings together a collection of studies, analyses, and innovative methodologies that represent the forefront of AI and ML In recent years, the pace of AI development has accelerated across industries, highlighting the need for robust, interpretable, and ethically aware models. As AI’s impact on society grows, so too does the responsibility of researchers and developers to produce systems that are both powerful and transparent. This issue addresses these pressing themes, featuring contributions that focus on interpretability, ethical AI, robust model design, and real-world applications This issue also includes insightful commentaries from leading voices in AI policy and development, offering perspectives on the regulatory and societal implications of AI research. Their expertise provides valuable context for readers who are not only interested in the technical aspects of AI and ML but also in their broader impacts.