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annotate doc/v2_planning/formulas.txt @ 1065:2bbc464d6ed0

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typo in doc
author James Bergstra <bergstrj@iro.umontreal.ca>
date Thu, 09 Sep 2010 17:50:50 -0400
parents bc246542d6ff
children 42ddbefd1e03
rev   line source
1051
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1 Math formulas
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2 =============
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3
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4 Participants
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5 ------------
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6 - Fred*
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7 - Razvan
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8 - Aaron
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9 - Olivier B.
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10 - Nicolas
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11
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12 TODO
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13 ----
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14 * define a list of search tag to start with
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15 * propose an interface(many inputs, outputs, doc style, hierrache, to search, html output?)
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16 * find existing repositories with files for formulas.
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17 * move existing formulas to pylearn as examples and add other basics ones.
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18 ** theano.tensor.nnet will probably be copied to pylearn.formulas.nnet and depricated.
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19
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20 Why we need formulas
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21 --------------------
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22
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23 Their is a few reasons why having a library of mathematical formula for theano is a good reason:
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24
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25 * Some formula have some special thing needed for the gpu.
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26 * Sometimes we need to cast to floatX...
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27 * Some formula have numerical stability problem.
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28 * Some formula gradiant have numerical stability problem. (Happen more frequently then the previous ones)
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29 * If theano don't always do some stability optimization, we could do it manually in the formulas
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30 * Some formula as complex to implement and take many try to do correctly.
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31
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32 Having a library help in that we solve those problem only once.
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33
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34 Formulas definition
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35 -------------------
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36
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37 We define formulas as something that don't have a state. They are implemented as python function
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38 that take theano variable as input and output theano variable. If you want state, look at what the
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39 learner commity will do.
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40
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41 Formulas doc must have
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42 ----------------------
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43
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44 * A latex mathematical description of the formulas(for picture representation in generated documentation)
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45 * Tags(for searching):
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46 * a list of lower lovel fct used
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47 * category(name of the submodule itself)
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48 * Tell if we did some work to make it more numerical stable. Do theano do the optimization needed?
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49 * Tell if the grad is numericaly stable? Do theano do the optimization needed?
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50 * Tell if work on gpu/not/unknow
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51 * Tell alternate name
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52 * Tell the domaine, range of the input/output(range should use the english notation of including or excluding)
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53
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54 List of existing repos
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55 ----------------------
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56
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57 Olivier B. ?
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58 Xavier G.: git@github.com:glorotxa/DeepANN.git, see file deepANN/{Activations.py(to nnet),Noise.py,Reconstruction_cost.py(to costs),Regularization.py(to regularization}
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59
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60 Proposed hierarchy
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61 ------------------
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62
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63 Here is the proposed hierarchy for formulas
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64
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65 pylearn.formulas.costs: generic / common cost functions, e.g. various cross-entropies, squared error,
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66 abs. error, various sparsity penalties (L1, Student)
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67
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68 pylearn.formulas.regularization: formulas for regularization
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69
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70 pylearn.formulas.linear: formulas for linear classifier, linear regression, factor analysis, PCA
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71
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72 pylearn.formulas.nnet: formulas for building layers of various kinds, various activation functions,
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73 layers which could be plugged with various costs & penalties, and stacked
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74
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75 pylearn.formulas.ae: formulas for auto-encoders and denoising auto-encoder variants
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76
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77 pylearn.formulas.noise: formulas for corruption processes
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78
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79 pylearn.formulas.rbm: energies, free energies, conditional distributions, Gibbs sampling
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80
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81 pylearn.formulas.trees: formulas for decision trees
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82
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83 pylearn.formulas.boosting: formulas for boosting variants
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84
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85 pylearn.formulas.maths for other math formulas
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86
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87 pylearn.formulas.scipy.stats: example to implement the same interface as existing lib
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88
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89 etc.