Hi Aja,
Thanks for a game and report.
I saw sgf, CNN can play ko fight. great.
our best CNN is about 220 to 310 Elo stronger which is consistent
Deeper network and rich info makes +300 Elo? impressive.
Aja, if your CNN+MCTS use Erica's playout, how strong will it be?
I think it will be
Hiroshi Yamashita: 37E4294EAD9142EA84D1031F3E1E9C7C@x60:
Hi Aja,
Thanks for a game and report.
I saw sgf, CNN can play ko fight. great.
our best CNN is about 220 to 310 Elo stronger which is consistent
Deeper network and rich info makes +300 Elo? impressive.
Aja, if your CNN+MCTS use Erica's
I thought that any layers beyond 3 were irrelevant. Probably I'm subsuming
your nn into what I learned about nn's and didn't read anything carefully
enough.
Can you help correct me?
s.
On Dec 23, 2014 6:47 AM, Aja Huang ajahu...@google.com wrote:
On Mon, Dec 22, 2014 at 12:38 PM, David Silver
A 3-layer network (input, hidden, output) is sufficient to be a universal
function approximator, so from a theoretical perspective only 3 layers are
necessary. But the gap between theoretical and practical is quite large.
The CNN architecture builds in translation invariance and sensitivity
Whilst its technically true that you can use an nn with one hidden layer to
learn the same function as a deeper net, you might need a combinatorally large
number of nodes :-)
scaling learning algorithms towards ai, by bengio and lecunn, 2007, makes a
convincing case along these lines.
Hello Hiroshi,
we want to release a version 2.0. There is still some clean-up work to do for a
release and progress is slow. But there is progress :)
https://sourceforge.net/p/fuego/tickets/
https://sourceforge.net/p/fuego/tickets/
Martin
I also wonder Fuego could release latest
From: Stefan Kaitschick stefan.kaitsch...@hamburg.de
mailto:stefan.kaitsch...@hamburg.de
...
Last move info is a strange beast, isn't it? I mean, except for ko
captures, it doesn't really add information to the position. The correct
prediction rate is such an obvious metric, but maybe
