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Here are 10 approaches to implement adaptive noise reduction, ordered by complexity/effectiveness:
### 1. Enhanced Spectral Subtraction
- Track noise floor during silence periods
- Use overlappin…
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### 🚀 The feature, motivation and pitch
I would like to implement the paper [Attributed Network Embedding via Subspace Discovery](https://arxiv.org/abs/1901.04095) by Zhang et al.
This paper…
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## 0. Paper
@article{arora-etal-2020-learning,
title = "Learning Lexical Subspaces in a Distributional Vector Space",
author = "Arora, Kushal and
Chakraborty, Aishik and
Che…
a1da4 updated
3 years ago
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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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Hi chicleee,
Thanks for the great job in advance.
To the best of my knowledge, I believe the repository lacks certain deep-homography and optical flow based methods and datasets.
Including, b…
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3-mode
aka multilinear subspace learning
Tucker decomposition
https://en.wikipedia.org/wiki/Multilinear_principal_component_analysis
my data is an n-array!
Tucker in 1966
then Kroonenberg
they …
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[Convergent Learning: Do different neural networks learn the same representations?](http://proceedings.mlr.press/v44/li15convergent.html)
Recent successes in training large, deep neural networks (DNN…
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### Hi! I am the one who currently using your Subspace-Regression-based-Face-Recognition as learning purpose. And when I try to run your code, all the classification algorithm can get accuracy properl…
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When pytorch is 1.7 in oneAPI AI toolkit, there is error in running case:
```
cd models/models/image_recognition/pytorch/common/
python main.py -d /home/wj/ImageNet/data/all -a resnet50 --epochs 10…
arthw updated
8 months ago
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> Quick notes on College level of Math or Stats for machine learning.
## Study resources
- [x] [Wiki: List of linear algebra topics](https://en.wikipedia.org/wiki/List_of_linear_algebra_topics)
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