If you come across a paper that is directly relevant to the problem you’re trying to solve but also makes claims that are unsupported by its own data (and contradict your own results), do you have to cite it? I feel that no credit should be given where none is due, and that debunking the claims is a waste of space.

For reference, this is the paper I’m talking about. The paper investigates adding attention layers on top of the standard CNN used by DQN on Atari. There are 6 variants considered, which differ in the location where the attention layers are added to the CNN.

Claim 1 (figure 2): “Here we can see the clear advantage of self-attention is able to provide with respect to sample efficiency.”

The baseline PPO learns faster or on-par with their 6 variants on 6 of the 10 games benchmarked.

Claim 2 (table 1): “These results clearly demonstrate the improved performance of multiple self-attention variants.”

Their best variant, SAN, performs better on 5 of the 10 games compared to the baseline PPO. Most of the other variants perform worse.

Claim 3 (conclusion): “We can also see clear improvements over baseline results with respect to 60% of environments tested”.

That is to say, the baseline PPO performs best on 4 games, and the proposed method performs best on the 6 other games if you cherry-pick the variant used on a per-game basis.

what is the current SOTA in voice cloning/ style transfer? Particularly something where you have a target voice you want to transfer a source voice audio or text to? Something similar to this https://github.com/andabi/deep-voice-conversion, is there a open source implementation to something close to SOTA?

Scaling PyTorch Transformer-XL training to 128 GPUs

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code: https://github.com/cybertronai/transformer-xl

experiments: https://medium.com/south-park-commons/scaling-transformer-xl-to-128-gpus-85849508ec35

The two Keras subs seem pretty dead, hoping I can find some help here.

I was able to use Keras to create a prediction from a time series, with input data looking like so:

But we would like to expand on this.

We have multiple products, which are each sold to multiple stores. I would like to create a tool where we throw data for each product at each store into a model, and then call “At this store, for this product, for this date, Keras predicts X”

I cannot seem to find an example that deals with having multiple rows for each date. An example of the full dataset is below. Seems like one way would be to make a column for each store/product combo and loop those through with a model for each, but I’m not sure if that would be ideal.

Hello everyone,

I would like to mine data from a facebook group to make a content generator for a facebook page, but I am quite clueless as to how to proceed. The use would be purely recreational, but google searchs did not yield anything interesting aside from Quora q&as.

Has anyone had any experience with making facebook page bots ? How can I mine data from a facebook group ?

Thank you for your replies.

> Our recent advances in natural language processing (NLP) and computer vision (CV) show how work in content understanding is producing benefits. In NLP, we’ve developed a shared multilingual embedding space that can act as a sort of lingua franca to help take action on harmful content even in low-resource languages. In CV, we’ve built on our industry-leading research to identify content in more parts of an image and achieve record-setting accuracy using hashtags for video understanding.

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Post: https://ai.facebook.com/blog/advances-in-content-understanding-self-supervision-to-protect-people