Improving recall from an associative memory

By B. Graham, David J. Willshaw. 1995

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1. Ursula Körner
2. Edgar Körner

Citations in the corpus

• Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect (2014, background): “In fact, an optimal threshold control as presumed above would actually require silent synapses in order to compute spike thresholds Hj~c’(j) in incompletely connected excitatory networks with Peffv1 [143,144] (so they should not be pruned).”
• Memory Capacities for Synaptic and Structural Plasticity (2010, background): “, 1996; Sommer and Palm, 1999), Improved threshold strategies (Buckingham and Willshaw, 1993; Graham and Willshaw, 1995), and retrieval with spiking neurons (Knoblauch and Palm, 2001; Knoblauch, 2003b) can significantly improve network capacity and retrieval accuracy in small memory networks.”
• Optimal synaptic learning in non-linear associative memory (2010, background): “Note also that this regime offers novel functional interpretations for strongly inhibitory circuits, for example, involving basket or chandelier cells [55], [48].”
• Neural Associative Memory with Optimal Bayesian Learning (2011, background): “By contrast, the common excitatory interpretation is efficient only for very sparse memory patterns and cannot implement optimal threshold control in a simple and biologically plausible way (Buckingham & Willshaw, 1993 ; Graham & Willshaw, 1995 ).”
• Improved bidirectional retrieval of sparse patterns stored by Hebbian learning (1999, unknown): “In the Willshaw model, suppression of cross-talk noise has been proposed by specifically adjusted individual thresholds during one-step retrieval (Buckingham and Willshaw, 1993; Graham and Willshaw, 1995).”