… novel approach to learning "useful" syntactic primitivefeatures, or primitive image fragments
(… sophy" in pattern recognition, 1-3~ which is applied here to a low-level learning process. …

… In addition to peak shift processing distinctive features in the data, we often learn patterns
and … We call this process “lateral learning,” which derives patterns from the same source but …

… Motion capture data from hu/ man locomotion was employed to learn an initial trajectory
pattern, which, after some modest tuning of the speed and amplitude parameters of the DMP …

… to learn action depends on the shape of its primitives 2 . Using a time-series analysis of error
patterns, here we show that humans learn the … a flexible combination of primitives that have …

… This framework first introduces primitive knowledge (ie, class-level part or … to learn to
complete prototypes with these priors. To avoid the prototype completion error caused by primitive …

… (ie, recognition of spatiotemporal patterns, not just spatial patterns as in traditional character
… when drawing two-dimensional single-stroke patterns. The 26 letters of the Graffiti alphabet …

… the unsupervised learning for certain tasks, such as pattern classification [… learning is still
lacking. In this work, we present computing primitive for all-optical SNN for supervised learning, …

… Besides the beneficial properties of DMPs in conjunction with imitation learning, trial-and-error
learning, reactive control, and compliant control, we also emphasize a bigger and still …

… Illustration of a task consisting of multiple interaction patterns, where each can be represented
as an Interaction Primitive. In this work, we want to learn multiple interaction patterns from …

… water, we must update the pattern of torques that our … pattern of neuromuscular activations
corresponds to some particular movement. Instead, the movement that arises from that pattern …