Fast Learning in Multi-Resolution Hierarchies

By John E. Moody. 1988

Citations in the corpus

• Deep learning in neural networks: An overview (2014, neutral): “…construction (e.g., Ash, 1989; Burgess, 1994; Fahlman, 1991; Fritzke, 1994; Gallant, 1988; Honavar & Uhr, 1988, 1993; Ivakhnenko, 1968, 1971; Moody, 1989; Parekh, Yang, & Honavar, 2000; Ring, 1991; Utgoff & Stracuzzi, 2002;Weng, Ahuja, & Huang, 1992) (see also Sections 5.3, 5.11), input…”
• On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models (2015, methodology): “As the history grows, to find an M with small bitsM + bitsH , step 4 uses sequential network construction: it regularly changes M ’s size by adding or pruning units and connections [111, 112, 8, 168, 59, 107, 304, 176, 141, 92, 143, 204, 53, 296, 106, 31, 57, 185, 283].”
• Flat Minima (1997, unknown): “Examples are \sequential network construction" (Fahlman & Lebiere, 1990; Ash, 1989; Moody, 1989), input pruning (Moody, 1992; Refenes et al., 1994), unit pruning (White, 1989; Mozer & Smolensky, 1989; Levin et al., 1994), weight pruning, e.g. \optimal brain damage" (LeCun et al., 1990), \optimal…”