dimensionality-driven-learning

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1

Hello, I want to reproduce your results. I set up everything with Python 3.6.6(and 3.6.10), TensorFlow 1.9.0, and Keras 2.2.0 ( which were the valid versions when the code was...

hsabaei

Hi, thanks for sharing your implementation. I have some questions about it: 1. Does it also work on tabular data? 2. Is the code tailored to the datasets used in...

nazaretl

Hi @YisenWang @xingjunm I happened to find that you are authors of both SL and D2L. It is common that results are different if they are from different authors because...

XinshaoAmosWang

different result on training

9

Dear Xingjun: I have tried your method to train the 12-layer-cnn on CIFAR-10 with 20% noise rate,I also observe the decrease and increase of LID score. but in my experiment....

jiangfanhan

Thank you for sharing your code! Can you resolve my confusion? When I observed network architectures in models.py in this github, it didn't match the description in ICML paper that...

ydkim1293

Training option

1

Hi, thank you for sharing the code. Is it possible to clarify the all training options (e.g., ``` python train_model.py -d mnist -m d2l -e 50 -b 128 -r 40...

pokaxpoka

LID increase with acc

1

Thank you for sharing the codes and your paper is very inspiring. But I test 'python train_newmodels.py -d cifar-10 -m d2l -e 50 -b 128 -r 0 ',and find the...

lxbin1995

Train on different dataset

1

Hi @xingjunm , I read your paper and its really intuitive. Thank you for sharing the code. Is it possible to use this code to train a different dataset than...

bhadresh74

I reworked the code into a new pytorch version and reproduced the results. The following two figures show the results of LID and train/test accuracy throughout training with clean(first figure)...

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