ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition. (arXiv:2105.08643v2 [cs.LG] UPDATED)

Many real-world scenarios, such as human activity recognition (HAR) in IoT,
can be formalized as a multi-task multi-view learning problem. Each specific
task consists of multiple shared feature views collected from multiple sources,
either homogeneous or heterogeneous. Common among recent approaches is to
employ a typical hard/soft sharing strategy at the initial phase separately for
each view across tasks to uncover common knowledge, underlying the assumption
that all views are conditionally independent. On the one hand, multiple views
across tasks …

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