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ALSH for solving mips sublinearly

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### mips 
ALSH for solving mips sublinearly

################ 
DATASET 
################ 
Link: http://files.grouplens.org/datasets/movielens/ml-latest-small.zip

To execute the code on a small dataset : 
1. run ./dataset_small.sh 
2. in ipynb files comment dataset = "datasets"+os.path.sep+"ml-latest" and uncomment dataset = "datasets"+os.path.sep+"ml-latest-small"

To execute the code on full dataset : 
1. run ./dataset.sh
2. in ipynb files uncomment dataset = "datasets"+os.path.sep+"ml-latest" and comment dataset = "datasets"+os.path.sep+"ml-latest-small"

################ 
PAPER 
################

Link to the paper : http://papers.nips.cc/paper/5329-asymmetric-lsh-alsh-for-sublinear-time-maximum-inner-product-search-mips.pdf

################# 
CODE 
################# 
ALSH.mips has stand alone code for complete implementation of LSH, SLSH and ALSH (helper file: utils.py)

##### 
Files: 
##### 
1. plots_paramas2.ipynb has functions for determining best parameters for U, m, r and c 
 It also has plots that show minimisations of rho functions. 
 
2. text.py has code to assemble netflix data from the zip file(s)

3. utils.py has code for helper functions of L2LSH, SLSH and ALSH

4. ALSH_MIPS.ipynb has code that tests on L2LSH, SLSH and ALSH. 
 It also has precision recall curves

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