A theory of task knowledge consolidation is presented that uses a large MTL network as the long-term memory structure and task rehearsal to overcome the ...
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PDF | A fundamental problem of life-long machine learning is how to consolidate the knowledge of a learned task within a long-term memory structure.
A theory of sequential consolidation of task knowledge which uses large MTL networks and a method of task rehearsal to overcome the stability-plasticity problem ...
Abstract. A fundamental problem of life-long machine learning is how to consolidate the knowledge of a learned task within a long-term mem-.
Using Knowledge Distillation (KD) and Elastic Weight Consolidation (EWC) helps a model retain information and performance from task A. Recall that each approach ...
A theory of task knowledge consolidation is presented that uses a large MTL network as the long-term memory structure and task rehearsal to overcome the ...
An efficient system using implicit feedback and lifelong learning approach to improve recommendation. Gautam Pal ; Consolidation Using Context-Sensitive Multiple ...
Sequential consolidation of learned task knowledge. Lecture Notes in AI, Canadian. AI'2004 217–232. Silver, D. L.; Poirier, R.; and Currie, D. 2008 ...
Jun 20, 2018 · We hypothesize that disrupting the DLPFC immediately after sequence learning would degrade the retention or consolidation of the sequence within ...
We investigate the effect of curriculum, i.e., a selection of tasks and the order in which they are learned, on the consolidation of task knowledge. Relevant ...