# LSTM-MATLAB
LSTM-MATLAB is Long Short-term Memory (LSTM) in MATLAB, which is meant to be succinct, illustrative and for research purpose only. It is accompanied with a paper for reference: [Revisit Long Short-Term Memory: An Optimization Perspective], NIPS deep learning workshop, 2014.
Creater & Maintainer
Qi Lyu
#FEATURES
- original Long short-term Memory
- all connect peephole
- support optimization methods like LBFGS and CG
- CPU or GPU acceleration
- Mapreduce parallelization
- gradient checking
- easy configuration
- baseline experiment
#ACKNOWLEDGEMENTS
The minFunc code folder included is provided by Mark Schmidt (http://www.cs.ubc.ca/~schmidtm).
MATLAB Mapreduce is provided by Quoc V. Le(http://cs.stanford.edu/~quocle/optimizationWeb/index.html).
#USAGE
To run the code, start from aStart.m. Data is generated by scripts in data directory on-the-fly. For faster LSTM implementation with complete features, see 'LSTMLayer' defined in [C++ version].
The dataset and labels etc follows the original LSTM paper in 1997.
License
----
MIT
[Revisit Long Short-Term Memory: An Optimization Perspective]:http://bigml.cs.tsinghua.edu.cn/~jun/pub/lstm-parallel.pdf
[C++ version]:https://github.com/huashiyiqike/NETLAB/blob/master/layernet/core/layer-inl.hpp
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温馨提示
lstm网络的建立、训练及应用实例,测试过,可用。(LSTM network establishment, training and application examples, tested, available.)
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LSTM-MATLAB-master.rar (271个子文件)
read_tiny_metadata_big_core.c 5KB
mcholC.c 4KB
mcholC.c 4KB
repmatC.c 4KB
read_tiny_binary_big_core.c 3KB
read_tiny_binary_gist_core.c 3KB
lbfgsC.c 2KB
lbfgsC.c 2KB
lbfgsProdC.c 2KB
mexutil.c 1KB
lbfgsAddC.c 802B
repmatC.dll 8KB
entries 6KB
entries 2KB
entries 2KB
entries 2KB
entries 1KB
entries 1013B
entries 594B
entries 576B
mexutil.h 317B
minFunc.m 42KB
minFunc.m 42KB
WolfeLineSearch.m 11KB
WolfeLineSearch.m 10KB
batch_equal_nomask_lstm.m 9KB
batch_cell_lstm.m 9KB
Server.m 7KB
testmodel.m 7KB
Main.m 7KB
read_tiny_big_metadata.m 6KB
ArmijoBacktrack.m 4KB
polyinterp.m 4KB
polyinterp.m 4KB
minFunc_processInputOptions.m 4KB
minFunc_processInputOptions.m 4KB
read_tiny_big_binary.m 3KB
rpc.m 3KB
read_tiny_gist_binary.m 3KB
ArmijoBacktrack.m 3KB
netInit.m 3KB
genadding.m 2KB
example_minFunc_LR.m 2KB
example_minFunc.m 2KB
example_minFunc.m 2KB
processRequest.m 2KB
java2matlab.m 2KB
conjGrad.m 2KB
slaveLoadCifar.m 2KB
conjGrad.m 2KB
serverRef.m 2KB
matlab2java.m 2KB
fastDerivativeCheck.m 2KB
example_minFunc_LR.m 2KB
slaveRef.m 1KB
example_derivativeCheck.m 1KB
Slave.m 1KB
autoTensor.m 1KB
autoGrad.m 1KB
mchol.m 1KB
mchol.m 1KB
clientLoadDataMinibatchNomask_ref.m 1KB
hook.m 1KB
autoHess.m 1KB
computeNumericalGradient.m 1KB
getReply.m 1KB
rosenbrock.m 1KB
aStart.m 1KB
derivativeCheck.m 1KB
dampedUpdate.m 995B
dampedUpdate.m 995B
emulateSlaveProcessRequest.m 982B
loadTinyImages.m 958B
lbfgs.m 924B
lbfgs.m 924B
gputype.m 911B
autoHess.m 901B
autoTensor.m 870B
slaveRun.m 844B
autoGrad.m 807B
softmaxLoss.m 805B
addpath_tica.m 749B
LogisticLoss.m 709B
lbfgsProd.m 696B
setup_paths.m 683B
lbfgsAdd.m 679B
taylorModel.m 677B
taylorModel.m 677B
sendRequest.m 672B
LogisticLoss.m 669B
lbfgsUpdate.m 614B
lbfgsUpdate.m 614B
slaveSoftmaxLoss.m 576B
mcholinc.m 564B
mcholinc.m 564B
rpcsum.m 560B
getRequest.m 488B
LogisticDiagPrecond.m 417B
LogisticDiagPrecond.m 417B
loadGroundTruth.m 397B
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