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Hi there,
First of all, thank you for sharing your work here! It's been incredibly insightful.
I have a question regarding the use of min-max scaling in the online adaptive learning stage of the…
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# EMNLP'23 | 京东: 深度语义召回中的超参自适应调整
* 参考论文:Adaptive Hyper-parameter Learning for Deep Semantic Retrieval
* 公司:京东
* 链接:https://aclanthology.org/2023.emnlp-industry.72.pdf
* 会议:EMNLP2023
# 太长不看
京东搜…
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- [Chapter 4. Beyond Gradient Descent](https://www.safaribooksonline.com/library/view/fundamentals-of-deep/9781491925607/ch04.html)
- [Alec Radford's animations for optimization algorithms](http://www…
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DeepChem offers various learning rate schedules, but all of them require you to specify the full schedule in advance. A popular alternative is to monitor the loss and reduce the learning rate wheneve…
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Implement adaptive learning rate for the pyDELFI NDE training @VMBoehm @eiffl
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A quote from PG about wikipedia:
> "What harm does it do if an online reference has a long tail of articles that are only
> interesting to a few people, so long as everyone can still find whatever th…
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I'm very interested in your paper “Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving”. Can you provide the corresponding code? Thank you very much…
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I am trying to create a GPU-based environment where a model is being trained say resnet18 where the number of environment can be greater than 1. I am not familiar with Jax but I am planning to learn i…
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So far, our learning rate is a fixed value, some paper and mllib are starting to use adaptive learning rate according to current iteration.
This is useful to decrease total iteration number.
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In the [SBERT repository](https://www.sbert.net/examples/training/adaptive_layer/README.html), I found the adaptive layers method referenced in this paper: [_**ESE**: Espresso Sentence Embeddings_](ht…