Group: http://groups.google.com/group/graphlabapi/topics
- std::unordered_map [1 Update]
- Libraries [2 Updates]
- Distributed Dual Decomposition is now implemented in GraphLab [1 Update]
Alex <alext...@gmail.com> Apr 19 01:53AM -0500
Hi,
I get this error when I use std::unordered_map.
/usr/include/c++/4.6/bits/c++0x_warning.h:32:2: error: #error This file
requires compiler and library support for the upcoming ISO C++ standard,
C++0x. This support is currently experimental, and must be enabled with the
-std=c++0x or -std=gnu++0x compiler options
How do I overcome this error?
Thanks,
Alex
On Mon, Mar 25, 2013 at 2:02 AM, Joseph Gonzalez <jego...@eecs.berkeley.edu
Chengi Liu <chengi...@gmail.com> Apr 17 11:46PM -0700
Yeah,
I mean.. I have a constructive criticism for graphlab team. I am a noob
in front of you guys..
You guys have to admit that both the current algorithms and the programming
style are quite sophisticated.
Baring CF toolkit (which has been popular because of netflix prize), as an
average "Joe", first I have to search the algorithm, and then you have a
distributed implementation where there is no documentation (except
references to again a very dense publication) and the option is to read the
code which is not that bad except it is because you guys are great coders
and your C++ code is also very dense.
So, why I asked this question is if you have something like Logistic/Linear
Regression out there, that is one less "dense" publication to read.
Also,it would greatly help me (us) if in the documentation you can include
how a particular algorithm can be implemented in GAS abstraction.
For
example: https://cwiki.apache.org/confluence/display/MAHOUT/Logistic+Regression
or maybe have a simple plain vanilla implementation without any crazy
optimization for some basic algorithms.
But let me just say, how much appreciative I am for you guys to develop
this awesome opensource project.
Thanks
On Monday, April 15, 2013 4:36:52 PM UTC-7, Chengi Liu wrote:
Yucheng Low <yl...@cs.cmu.edu> Apr 18 09:09AM -0700
We do have rather extensive documentation here: http://docs.graphlab.org/ .
The code in toolkits/ tend to quite a bit more optimized (thus less readable). But for some stuff there are simpler versions (i.e. simple_undirected_triangle_count), or in demoapps/simple_pagerank which are quite heavily commented to be readable.
Instead of Logistic Regression / Linear Regression, our "simple" case is PageRank, for which we do have a walkthrough here:
http://docs.graphlab.org/using_graphlab.html
Yucheng
Danny Bickson <danny....@gmail.com> Apr 18 07:33AM -0700
Many thanks to Dhruv Batra from Virginia Tech for his great contribution.
Read more here:
http://bickson.blogspot.com/2013/04/distributed-dual-decomposition-ddd-in.html
Dr. Danny Bickson
Project Scientist, Machine Learning Dept.
Carnegie Mellon University
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