Back-merge to dev for doc fixes + cherry-picks

Back-merge these doc fixes:

  clarify project origin
  [docs] fix citation bibtex

All other changes are spurious commits from cherry-picking.

diff --cc docs/installation.md
index b9360a9c6316adc9d22e69da911e6c952efc3129,1ac6c08b6caffbade045475ce23dd94050ee6675..5732135303309e77bae56b18971a5de33fae3253
--- 1/docs/installation.md
--- 2/docs/installation.md
+++ b/docs/installation.md
@@@ -218,29 -218,8 +218,29 @@@ Be sure to set your MATLAB and Python p
  
  *Speed*: for a faster build, compile in parallel by doing `make all -j8` where 8 is the number of parallel threads for compilation (a good choice for the number of threads is the number of cores in your machine).
  
- Now that you have installed Caffe, check out the [MNIST demo](mnist.html) and the pretrained [ImageNet example](imagenet.html).
+ Now that you have installed Caffe, check out the [MNIST tutorial](gathered/examples/mnist.html) and the [reference ImageNet model tutorial](gathered/examples/imagenet.html).
  
 +### Compilation using CMake (beta)
 +
 +In lieu of manually editing `Makefile.config` to tell Caffe where dependencies are located, Caffe also provides a CMake-based build system (currently in "beta").
 +It requires CMake version >= 2.8.8.
 +The basic installation steps are as follows:
 +
 +    mkdir build
 +    cd build
 +    cmake ..
 +    make all
 +    make runtest
 +
 +#### Ubuntu 12.04
 +
 +Note that in Ubuntu 12.04, Aptitude will install version CMake 2.8.7 by default, which is not supported by Caffe's CMake build (requires at least 2.8.8).
 +As a workaround, if you are using Ubuntu 12.04 you can try the following steps to install (or upgrade to) CMake 2.8.9:
 +
 +    sudo add-apt-repository ppa:ubuntu-sdk-team/ppa -y
 +    sudo apt-get -y update
 +    sudo apt-get install cmake
 +
  ## Hardware Questions
  
  **Laboratory Tested Hardware**: Berkeley Vision runs Caffe with K40s, K20s, and Titans including models at ImageNet/ILSVRC scale. We also run on GTX series cards and GPU-equipped MacBook Pros. We have not encountered any trouble in-house with devices with CUDA capability >= 3.0. All reported hardware issues thus-far have been due to GPU configuration, overheating, and the like.