Wed, 08 Apr 2009 19:53:18 -0400 |
James Bergstra |
better scan
|
Tue, 07 Apr 2009 18:00:24 -0400 |
James Bergstra |
added README for lib
|
Tue, 07 Apr 2009 17:56:58 -0400 |
James Bergstra |
adding scan1 op
|
Thu, 02 Apr 2009 17:57:51 -0400 |
James Bergstra |
small correction to exponential_mean
|
Thu, 02 Apr 2009 15:08:42 -0400 |
James Bergstra |
added exponential_mean
|
Thu, 02 Apr 2009 15:08:22 -0400 |
James Bergstra |
added updates parameter to sgd
|
Wed, 01 Apr 2009 19:48:47 -0400 |
James Bergstra |
merge
|
Wed, 01 Apr 2009 19:48:32 -0400 |
James Bergstra |
changes to tzanetakis and wavread
|
Mon, 30 Mar 2009 20:48:04 -0400 |
Joseph Turian |
merge
|
Thu, 20 Nov 2008 06:38:06 -0500 |
Joseph Turian |
Added preprocessing back in
|
Mon, 30 Mar 2009 19:51:13 -0400 |
James Bergstra |
adding wavread and tzanetakis dataset
|
Mon, 30 Mar 2009 16:15:24 -0400 |
James Bergstra |
removed Member calls from logistic regression
|
Mon, 30 Mar 2009 16:00:29 -0400 |
James Bergstra |
moved test_filetensor to tests subdir
|
Mon, 30 Mar 2009 15:44:42 -0400 |
James Bergstra |
added sgd_minimizer back into sgd
|
Mon, 30 Mar 2009 12:26:01 -0400 |
James Bergstra |
merge
|
Mon, 30 Mar 2009 12:25:42 -0400 |
James Bergstra |
updating minimizer, sgd to new theano. added sgd tests
|
Wed, 11 Mar 2009 11:13:29 -0400 |
desjagui |
Changed RModule to deprecated.RModule .... temporarily until they are fixed with
|
Wed, 11 Mar 2009 00:09:22 -0400 |
Joseph Turian |
Trying to fix gradient in logfactorial
|
Tue, 10 Mar 2009 20:58:16 -0400 |
Joseph Turian |
Updated comments in nlpoisson cost
|
Tue, 10 Mar 2009 19:03:38 -0400 |
Joseph Turian |
Refactored poisson loss.
|
Tue, 10 Mar 2009 15:58:52 -0400 |
Joseph Turian |
Added a gradient test for nlpoisson.
|
Mon, 09 Mar 2009 03:11:20 -0400 |
Joseph Turian |
Added preliminary code for computing negative log Poisson cost
|
Mon, 09 Mar 2009 00:25:46 -0400 |
Joseph Turian |
Added a cost to sandbox, building out Poisson regressor
|
Tue, 03 Mar 2009 11:37:56 -0500 |
Frederic Bastien |
added pylearn.datasets.MNIST.first_10 and pylearn.datasets.MNIST.first_100. They are usefull to test with small dataset.
|