Laurent de Vito

I forgot: Your dataset will be acknowledged as follows ``` class MixHopSyntheticDataset(InMemoryDataset): r"""The MixHop synthetic dataset from the `"MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" `_ paper, containing...

No.

If I remember well, for binary classification, it is just a matter of changing the objective function. I will have a look at it if I have some time. Will...

Implementation for binary classification is done. I just added a test. I do not know at the moment how to extend it to multiclass. At the leaves, we have scores,...

That's possible. It is pretty easy to use a subset of features for the construction of the trees. For the linear regression, it is also likely to be straightforward. However,...

I haven't tested any other optimizer from this package, but I know for sure that many others have this attribute `use_gc` (short for use gradient centralization).

Thanks for the help. Yesterday I installed PyTorch 2.1 and it seems that ipex is not PyTorch 2.1 ready, since I got ``` Traceback (most recent call last): import intel_extension_for_pytorch...

I confirm that my code (see above) works fine with pytorch and ipex 2.1 if I set `model, optimizer = ipex.optimize(model, optimizer=optimizer, inplace=True)` Thanks to @zhuhaozhe !

Thanks for the prompt answer. I assume this is for Type-1 AA. So, it only works for small to medium problems.