Update README

lovepan1 · Apr 22, 2019 · 5e8c5ae · 5e8c5ae
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 # CIFAR Experiments
-This directory contains all the CIFAR experiments in the paper, where there are three pruning methods in total:  
+This directory contains all the CIFAR experiments in the paper, where there are four pruning methods in total:  
 
 1. [L1-norm based channel pruning](https://arxiv.org/abs/1608.08710)
 2. [Network Slimming](https://arxiv.org/abs/1708.06519)
 3. [Soft filter pruning](https://www.ijcai.org/proceedings/2018/0309.pdf)
 4. [Non-structured weight-level pruning](https://arxiv.org/abs/1506.02626)
 
-For each method, we give example commands for baseline training, finetuning, scratch-E training and scratch-B training.
+For each method, we give example commands for baseline training, finetuning, scratch-E training and scratch-B training.  
+
+We also give our implementation for [Lottery Ticket Hypothesis](https://arxiv.org/abs/1803.03635).
 
 ## Implementation
 Our code is based on [network-slimming](https://github.com/Eric-mingjie/network-slimming) and [pytorch-classification](https://github.com/bearpaw/pytorch-classification).