Self-Taught Learning
From Ufldl
(→Learning features) |
(→Learning features) |
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\}</math> (if we use the replacement representation, and use <math>\textstyle a_l^{(i)}</math> to represent the | \}</math> (if we use the replacement representation, and use <math>\textstyle a_l^{(i)}</math> to represent the | ||
<math>\textstyle i</math>-th training example), or <math>\textstyle \{ | <math>\textstyle i</math>-th training example), or <math>\textstyle \{ | ||
- | ((x_l^{(1)}, a_l^{(1)}), y^{(1)}), ((x_l^{(2)}, a_l^{(1)}), y^{(2)}), \ldots | + | ((x_l^{(1)}, a_l^{(1)}), y^{(1)}), ((x_l^{(2)}, a_l^{(1)}), y^{(2)}), \ldots, |
((x_l^{(m_l)}, a_l^{(1)}), y^{(m_l)}) \}</math> (if we use the concatenated | ((x_l^{(m_l)}, a_l^{(1)}), y^{(m_l)}) \}</math> (if we use the concatenated | ||
representation). In practice, the concatenated representation often works | representation). In practice, the concatenated representation often works |