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Training a HyperDimensional Computing Classifier using a Threshold on its Confidence
Hyperdimensional computing (HDC) has become popular for light-weight and energy-efficient machine learning, suitable for wearable Internet-of-Things (IoT) devices and near-sensor or on-device processing.
Deep set conditioned latent representations for action recognition
The proposed method achieves an improvement of around 1. 49% mAP in atomic action recognition and 17. 57% mAP in composite action recognition, over a I3D-NL baseline, on the CATER dataset.
Ranked #1 on
Atomic action recognition
on CATER
(using extra training data)
Deep Learning of Intrinsically Motivated Options in the Arcade Learning Environment
As an alternative to the widespread method of a weighted sum of rewards, Explore Options let the agent call an intrinsically motivated agent in order to observe and learn from interesting behaviors in the environment.
