Unsupervised Learning of Mixtures of Multiple Causes in Binary Data

By Eric Saund. 1993

Citations in the corpus

• Deep learning in neural networks: An overview (2014, background): “…1990; Miller, 1994; Mozer, 1991; Oja, 1989; Palm, 1992; Pearlmutter &Hinton, 1986; Ritter & Kohonen, 1989; Rubner & Schulten, 1990; Sanger, 1989; Saund, 1994; von der Malsburg, 1973; Watanabe, 1985; Willshaw & von der Malsburg, 1976); see also post-2000 work (e.g., Carreira-Perpinan, 2001;…”
• Feature Extraction Through LOCOCODE (1999, unknown): “Recently there also has been much work on COCOFs encouraging biologically plausible sparse distributed codes (e.g., Field, 1987; Barlow, 1983; Mozer, 1991; Földiák, 1990; Földiák & Young, 1995; Palm, 1992; Zemel & Hinton, 1994; Field, 1994; Saund, 1994; Dayan & Zemel, 1995; Li, 1995; Olshausen & Fie”
• Competition and Multiple Cause Models (1995, methodology): “A simple example which motivated the model and the need for competition is one of extracting a number of independent horizontal and vertical bars on an input pixel grid (F ¨ oldi ´ ak, 1990; Saund, 1994b; Zemel, 1993).”
• The Helmholtz Machine (1995, unknown): “a6=j 1 q`a ` ;` 1 a;i 1+ ` ;` 1 a;i ! (21)”