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## 論文URL
https://arxiv.org/pdf/2008.13535v2.pdf
## 著者
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi
Google Inc.
## 会議
WWW '21: Proceedings…
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Hi, I am really interested in your ideas, and hurry to implement a toy example to test it.
I find that you write a comprehensive and complicated extension in `autoint` to automatically "extract" th…
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## 🐛 Bug
I'm trying to export a deep neural network (AutoInt) that takes in 2 inputs (features and a mask) to onnx. However, when I run torch.onnx.export, it only exports a model with the first inp…
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Could you please share us all the parameters used? Thanks!
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From the implementation of the AutoInt code, I noticed that the dense features are never passed into the Attention layer. Instead they're simply passed through a simple Feed Forward Network and combin…
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Please refer to the [FAQ](https://deepctr-doc.readthedocs.io/en/latest/FAQ.html) in doc and search for the [related issues](https://github.com/shenweichen/DeepCTR/issues) before you ask the question.
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- 1. how to return the model structure? something like print(model) in pytorch.
- 2. when I use the NodeConfig (Modemodel) to train a 2 layers, each layer 512 trees model, it is really really slow, …
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BÚÉK!
Holnap 15:30-kor lesz az első ML_JC ebben az évben.
Én a [jax](https://github.com/google/jax) nevű, viszonylag új és áramlvonalas deep learning frameworkról beszélni,
továbbá az implici…
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Erre kíváncsi lennék:
Exploring Weight Agnostic Neural Networks
Tuesday, August 27, 2019
Posted by Adam Gaier, Student Researcher and David Ha, Staff Research Scientist, Google Research, Tokyo
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1. No embeddings for continuous values
2. No skip connections between attention blocks
diff7 updated
4 years ago