AI & Machine Learning

PAC learning PDFA from data streams

Ali Nemati3 days ago31 sec read4 views0 listens

Researchers have published an extended version of their work on learning state machines from data streams, including a formal proof of PAC-bounds and a new heuristic for handling incomplete data. This development is significant for developers and tech professionals working with real-time systems, as it provides a method to learn state machine models directly from streaming data without requiring all data upfront. The research also offers theoretical improvements in runtime efficiency while maintaining algorithm correctness.

Read the full article at arXiv cs.LG (ML)

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