ozansener / active_learning_coreset Goto Github PK

When you are running the full_gurobi_parser, where does the 'feature_vectors_pickled' come from?

HI, I'm wondering what's the value you used for upper bound and delta in your experiments. I only found the upper bound \Chi=1e-4*n in the paper. Is this the UB used in the code? How about the delta? Thank you very much!

Hi,
Just wondering if you could specify how to run the package and reproduce the results. From your paper I understand that the implementation is in Tensorflow. So probably for cifar10 that is tf_base -> cifar10_train -> train_cifar ?

There is implementation in PyTorch additional_baselines -> main as well. Is that just re-implementation in PyTorch?

Dear author:
When I run your code "main.py" under the folder of additional_baselines, there exists an error that "can not find the file named 'fisher_20000.bn' ". And I couldn't find any code files to create that file. Could you please tell me the procedure that you produce this file? Thank you very much.

Hello,

If I understood correctly, a point B is associated to a cluster A if they are closer than a fixed distance δ. Since the neural network is Lipschitz continuous, the output of the neural network cannot change much for a given δ. Therefore, if the error of the point A (contained in the coreset) is assumed to be zero, the error of B will be small (bounded).

However, if points A and B are closer than δ but they have different targets, the error could be arbitrarily large, right? Would it be sensible to only cover points that have the same target?

Thanks in advance!

Hi,
I think the file greedy_facility_location.py is not executable because I can see in the
line 31
#for lab in dat['gt_f'].shape[0]): There are some unbalanced parenthesis

line 38
no = numpy.argmax(d) . d is not defined.

It would be great if you can share your code which you used for the results obtained in the ICLR paper