The streaming nature of training data makes it harder to have a pre- defined training set, which fully represents the current and future distribution of exploited data. The learning phase must therefore be continuous and distributed over time [3].
Jan 9, 2023
Jan 9, 2023 · In this paper, we investigate the classification performance of a variety of algorithms that belong to various research field, i.e. Continual, ...
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This paper investigates the classification performance of a variety of algorithms that belong to various research, i.e . —In real-world contexts, ...
In real-world contexts, sometimes data are available in form of Natural DataStreams, i.e. data characterized by a streaming nature, unbalanceddistribution, ...
Abstract: This invention discloses a deep reinforcement learning based adaptive bitrate selection method and system for real-time streaming, where deep ...
A natural approach for these incremental tasks are adaptive learning algorithms, incre- mental learning algorithms that take into account concept drift ...
On The Challenges to Learn from Natural Data Streams · GUIDO BORGHI et. al. Related Grants: Score, Title, Type, PI(s), Organization, Funding (M), Effective Date ...
Oct 10, 2023 · 1.Utilize event-driven architectures · 2.Integrate data sources and applications seamlessly · 3.Invest in real-time data governance and quality ...
Aug 21, 2023 · 10 Data Streaming Challenges Enterprises Face Today · 1. Handling Unbounded Data Streams · 2. Navigating Stream Processing Complexity · 3. Adapting ...