Motion Memory: Invariant representations of sequences in cortical L2/3 by Hierarchical Temporal Memory

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00328425" target="_blank" >RIV/68407700:21230/18:00328425 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21340/18:00328425 RIV/68407700:21730/18:00328425

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1877050918323792" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050918323792</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2018.11.091" target="_blank" >10.1016/j.procs.2018.11.091</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Motion Memory: Invariant representations of sequences in cortical L2/3 by Hierarchical Temporal Memory

Popis výsledku v původním jazyce

We aim to form stable representations of temporal sequences with key focus on semantic learning and streaming data. The state of the art in the Hierarchical Temporal Memory is represented by Numenta’s recently published “ColumnPooler” which emulates functionality of cortical L2/3 layer, forms stable allocentric representations of temporal sequences and/or objects, and has been applied to sensory-motor learning. Our designed experiments evaluate the ColumnPooler for such task and uncover its current limitations. Presented “Motion Memory” design defines needed modifications in order to be effectively used for sequence representation, namely: Semantic distance between the representations; Online learning on streams; ability to represent time; and representation of motion from static sensor. One of the main problems with the current design is the lack of semantic meaning in (continuously updated) representations of the object. The proposed improvement enables MotionMemory to do unsupervised learning on streaming data and resulting representation have semantic meaning, this has many practical applications in sensory processing (ie. vision), or hierarchical learning.

Název v anglickém jazyce

Motion Memory: Invariant representations of sequences in cortical L2/3 by Hierarchical Temporal Memory

Popis výsledku anglicky

We aim to form stable representations of temporal sequences with key focus on semantic learning and streaming data. The state of the art in the Hierarchical Temporal Memory is represented by Numenta’s recently published “ColumnPooler” which emulates functionality of cortical L2/3 layer, forms stable allocentric representations of temporal sequences and/or objects, and has been applied to sensory-motor learning. Our designed experiments evaluate the ColumnPooler for such task and uncover its current limitations. Presented “Motion Memory” design defines needed modifications in order to be effectively used for sequence representation, namely: Semantic distance between the representations; Online learning on streams; ability to represent time; and representation of motion from static sensor. One of the main problems with the current design is the lack of semantic meaning in (continuously updated) representations of the object. The proposed improvement enables MotionMemory to do unsupervised learning on streaming data and resulting representation have semantic meaning, this has many practical applications in sensory processing (ie. vision), or hierarchical learning.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Procedia Computer Science

ISBN

—

ISSN

1877-0509

e-ISSN

1877-0509

Počet stran výsledku

6

Strana od-do

400-405

Název nakladatele

Elsevier B.V.

Místo vydání

New York

Místo konání akce

Praha

Datum konání akce

22. 8. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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