On setting unit thresholds in an incompletely connected associative net Network: Comput

By J. Buckingham, David J. Willshaw. 1993

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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.”
Improved bidirectional retrieval of sparse patterns stored by Hebbian learning (1999, unknown): “Section 4.3 contains a refined analysis of the finite size Willshaw model: an improved combinatorial calculation of retrieval error probabilities is derived (Proposition 4.2) that allows much faster numerical evaluation than the previously given formula (Buckingham and Willshaw, 1993).”
Neural Associative Memory with Optimal Bayesian Learning (2011, background): “Exact potential distributions are well known and can be used to compute optimal firing thresholds (Palm, 1980; Buckingham & Willshaw, 1992, 1993; Knoblauch, 2008; Knoblauch et al., 2010).”
Iterative retrieval of sparsely coded associative memory patterns (1996, background): “Basically,threshold setting in a neural network can be carried out by setting a global threshold = j [Palm, 1980, Gibson and Robinson, 1992], or by setting individual threshold values j [Marr, 1971, Buckingham and Willshaw, 1993].”
Information storage capacity of incompletely connected associative memories (1998, methodology): “69 for full connectivity, con rming Palm's result of C = log(2).”