Subject: Re: [boost] [ublas] Supporting DNNs with Tensors/Multidimensional Arrays
From: Cem Bassoy (cem.bassoy_at_[hidden])
Date: 2018-09-06 17:05:22
I totally agree. DNNs are just one part. Lets put in more numerical
algorithms using tensors, matrices and vectors. However, IMHO I think that
the community needs better documentation, interfaces, (possibly
implementation) of basic tensor, matrix and vector operations. I am now
also changing the interface of the tensor data structure for being able to
be an alias for matrix and vector.
Am Sa., 1. Sep. 2018 um 11:54 Uhr schrieb David Bellot <
>> 1. if it make sense for boost to support basic operations for DNNs?
>> 2. what are the obligatory, necessary basic operations for creating DNN
>> building blocks?
>> 3. if there are any additional data structure parameters that needs to be
>> added for (efficiently) supporting DNNs?
> DNN are certainly interesting models in machine learning, but they
> represent a very small part of what we can do and what really works in real
> Tensors can be applied to many more situations. On top of it, tensors can
> be applied to many other field of science.
> What would be interesting is to start thinking more generically and not
> focus too much on just DNN, especially if we want to have machine learning
> in ublas (which was another successful GSOC this year by the way).
> I'm glad to see we have tensors, I'm happy to see we have basics stats and
> Let's go to the next step and have some more numerical techniques related
> to linear algebra in ublas.
> Open discussion now .....
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