(1) Generate a random BigInteger in range of [0, 2^(numBits)-1]
BigInteger(int numBits, Random rnd)
(1) Generate a random BigInteger in range of [0, 2^(numBits)-1]
BigInteger(int numBits, Random rnd)
Use -Xmx to set the maximum heap size (which may use hard drive space as Java heap). e.g. set the max heap size to 10GB:
java -Xmx10g MainClass
It may be further optimized using garbage collectors such ConcurrentMarkSweep:
java -Xmx10g -XX:+UseConcMarkSweepGC MainClass
This is reading notes on Professional C++ by Marc Gregoire, but also includes other notes.
std::string str = std::bitset<8>(123).to_string();</code>
echo $(/usr/libexec/java_home)
If you don’t want fields such as “[Online]”, “Available: …” appear in IEEEtran bibliography items:
1. Go to installation folder of IEEEtan bst.
(on my Mac OS with Texlive, the folder is /usr/local/texlive/2016/texmf-dist/bibtex/bst/IEEEtran)
2. Backup and then edit IEEEtran.bst, search “FUNCTION XXX” (XXX could be “inproceedings”, “inbook”, etc.), and comment out “format.url output”
3. run “texhash”
4. recompile .bib and .tex files.
Reference:https://tex.stackexchange.com/questions/45160/remove-url-in-ieeetran-bibliography
Reference: https://www.tensorflow.org/versions/r0.10/api_docs/python/nn/activation_functions_
1. Smooth nonlinearities:
(tf.nn.)sigmoid, tanh, elu, softplus, softsign
2. Continuous but not everywhere differentiable:
(tf.nn.)relu, relu6
3. Random regularization:
(tf.nn.)dropout
e.g. for tf.contrib.learn.DNNClassifier, the default activation function in __init__ is relu:
__init__( ..., activation_fn=tf.nn.relu, ...)
hostnamectl set-hostname HOSTNAME-TO-USE
Reference: https://www.tensorflow.org/get_started/get_started
1. Multiple level APIs:
(1) lowest level: TensorFlow Core, if you need fine controls on the model
(2) higher levels: built on Core, easier to use, e.g. tf.contrib.learn
2. Tensor: an array of primitive values. Rank: how many dimensions. Shape: a vector, containing the numbers of elements in each dimension.
e.g. [[[1., 2., 3.]], [[7., 8., 9.]]] has rank 3, shape [2,1,3]
3. Import library
import tensorflow as tf