Slow down to go better: A survey on slow feature analysis
Temporal data contain a wealth of valuable information, playing an essential role in various
machine-learning tasks. Slow feature analysis (SFA), one of the most classic temporal …
machine-learning tasks. Slow feature analysis (SFA), one of the most classic temporal …
[HTML][HTML] Continual curiosity-driven skill acquisition from high-dimensional video inputs for humanoid robots
In the absence of external guidance, how can a robot learn to map the many raw pixels of
high-dimensional visual inputs to useful action sequences? We propose here Continual …
high-dimensional visual inputs to useful action sequences? We propose here Continual …
An intrinsic value system for developing multiple invariant representations with incremental slowness learning
Curiosity Driven Modular Incremental Slow Feature Analysis (CD-MISFA;) is a recently
introduced model of intrinsically-motivated invariance learning. Artificial curiosity enables …
introduced model of intrinsically-motivated invariance learning. Artificial curiosity enables …
Incremental episodic segmentation and imitative learning of humanoid robot through self-exploration
Imitation learning through self-exploration is an essential mechanism in developing
sensorimotor skills for human infants as well for robots. We assume that a primitive sense of …
sensorimotor skills for human infants as well for robots. We assume that a primitive sense of …
Low complexity proto-value function learning from sensory observations with incremental slow feature analysis
M Luciw, J Schmidhuber - … Networks and Machine Learning–ICANN 2012 …, 2012 - Springer
Abstract We show that Incremental Slow Feature Analysis (IncSFA) provides a low
complexity method for learning Proto-Value Functions (PVFs). It has been shown that a …
complexity method for learning Proto-Value Functions (PVFs). It has been shown that a …
Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application.
H Yang, Y Zhao, G Su, X Liu, S Jin, H Fan… - Traitement du …, 2021 - search.ebscohost.com
The conventional slow feature analysis (SFA) algorithm has no support of computational
theory of vision for primates, nor does it have the ability to learn the global features with …
theory of vision for primates, nor does it have the ability to learn the global features with …
Optimal curiosity-driven modular incremental slow feature analysis
Consider a self-motivated artificial agent who is exploring a complex environment. Part of
the complexity is due to the raw high-dimensional sensory input streams, which the agent …
the complexity is due to the raw high-dimensional sensory input streams, which the agent …
Developmental approach for behavior learning using primitive motion skills
Imitation learning through self-exploration is essential in developing sensorimotor skills.
Most developmental theories emphasize that social interactions, especially understanding of …
Most developmental theories emphasize that social interactions, especially understanding of …
Design and Application of a Slow Feature Algorithm Coupling Visual Selectivity and Multiple Long Short-Term Memory Networks.
Y Zhao, H Yang, G Su - Traitement du Signal, 2021 - search.ebscohost.com
In the traditional slow feature analysis (SFA), the expansion of polynomial basis function
lacks the support of visual computing theories for primates, and cannot learn the uniform …
lacks the support of visual computing theories for primates, and cannot learn the uniform …