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shenweichen · Nov 3, 2022 · d4425e8 · d4425e8
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diff --git a/docs/pics/EDCN.jpg → docs/pics/EDCN.png b/docs/pics/EDCN.jpg → docs/pics/EDCN.png
diff --git a/docs/source/Features.md b/docs/source/Features.md
@@ -304,6 +304,17 @@ feature. FEFM has significantly lower model complexity than FFM and roughly the
 
 [Pande H. Field-Embedded Factorization Machines for Click-through rate prediction[J]. arXiv preprint arXiv:2009.09931, 2020.](https://arxiv.org/pdf/2009.09931)
 
+### EDCN(Enhancing Explicit and Implicit Feature Interactions DCN)
+
+EDCN introduces two advanced modules, namelybridge moduleandregulation module, which work collaboratively tocapture the layer-wise interactive signals and learn discriminativefeature distributions for each hidden layer of the parallel networks.
+
+[**EDCN Model API**](./deepctr.models.edcn.html)
+
+![EDCN](../pics/EDCN.png)
+
+[Chen B, Wang Y, Liu Z, et al. Enhancing explicit and implicit feature interactions via information sharing for parallel deep ctr models[C]//Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2021: 3757-3766.](https://dlp-kdd.github.io/assets/pdf/DLP-KDD_2021_paper_12.pdf)
+
+
 ## Sequence Models
 
 ### DIN (Deep Interest Network)
@@ -413,15 +424,6 @@ information routing across tasks in a general setup.
 
 [Tang H, Liu J, Zhao M, et al. Progressive layered extraction (ple): A novel multi-task learning (mtl) model for personalized recommendations[C]//Fourteenth ACM Conference on Recommender Systems. 2020.](https://dl.acm.org/doi/10.1145/3383313.3412236)
 
-### EDCN(Enhancing Explicit and Implicit Feature Interactions DCN)
-
-EDCN introduces two advanced modules, namelybridge moduleandregulation module, which work collaboratively tocapture the layer-wise interactive signals and learn discriminativefeature distributions for each hidden layer of the parallel networks.
-
-[**EDCN Model API**](./deepctr.models.edcn.html)
-
-![EDCN](../pics/EDCN.png)
-
-[Chen B, Wang Y, Liu Z, et al. Enhancing explicit and implicit feature interactions via information sharing for parallel deep ctr models[C]//Proceedings of the 30th ACM International Conference on Information & Knowledge Management. 2021: 3757-3766.](https://dlp-kdd.github.io/assets/pdf/DLP-KDD_2021_paper_12.pdf)
 
 
 ## Layers

diff --git a/docs/source/History.md b/docs/source/History.md
@@ -1,5 +1,5 @@
 # History
-- 11/05/2022 : [v0.9.3](https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.3) released.Add [EDCN]().
+- 11/05/2022 : [v0.9.3](https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.3) released.Add [EDCN](./Features.html#edcn-enhancing-explicit-and-implicit-feature-interactions-dcn).
 - 10/15/2022 : [v0.9.2](https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.2) released.Support python `3.9`,`3.10`.
 - 06/11/2022 : [v0.9.1](https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.1) released.Improve compatibility with tensorflow `2.x`.
 - 09/03/2021 : [v0.9.0](https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.0) released.Add multitask learning models:[SharedBottom](./Features.html#sharedbottom),[ESMM](./Features.html#esmm-entire-space-multi-task-model),[MMOE](./Features.html#mmoe-multi-gate-mixture-of-experts) and [PLE](./Features.html#ple-progressive-layered-extraction). [running example](./Examples.html#multitask-learning-mmoe)
@@ -11,8 +11,8 @@
 - 10/11/2020 : [v0.8.2](https://github.com/shenweichen/DeepCTR/releases/tag/v0.8.2) released.Refactor `DNN` Layer.
 - 09/12/2020 : [v0.8.1](https://github.com/shenweichen/DeepCTR/releases/tag/v0.8.1) released.Improve the reproducibility & fix some bugs.
 - 06/27/2020 : [v0.8.0](https://github.com/shenweichen/DeepCTR/releases/tag/v0.8.0) released.
-  - Support `Tensorflow Estimator` for large scale data and distributed training. [example: Estimator with TFRecord](https://deepctr-doc.readthedocs.io/en/latest/Examples.html#estimator-with-tfrecord-classification-criteo) 
-  - Support different initializers for different embedding weights and loading pretrained embeddings. [example](https://deepctr-doc.readthedocs.io/en/latest/FAQ.html#how-to-use-pretrained-weights-to-initialize-embedding-weights-and-frozen-embedding-weights)
+  - Support `Tensorflow Estimator` for large scale data and distributed training. [example: Estimator with TFRecord](./Examples.html#estimator-with-tfrecord-classification-criteo) 
+  - Support different initializers for different embedding weights and loading pretrained embeddings. [example](./FAQ.html#how-to-use-pretrained-weights-to-initialize-embedding-weights-and-frozen-embedding-weights)
   - Add new model `FwFM`.
 - 05/17/2020 : [v0.7.5](https://github.com/shenweichen/DeepCTR/releases/tag/v0.7.5) released.Fix numerical instability in `LayerNormalization`.
 - 03/15/2020 : [v0.7.4](https://github.com/shenweichen/DeepCTR/releases/tag/v0.7.4) released.Add [FLEN](./Features.html#flen-field-leveraged-embedding-network) and `FieldWiseBiInteraction`.

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -44,7 +44,7 @@ News
 -----
 11/05/2022 : Add `EDCN` . `Changelog <https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.3>`_
 
-10/15/2022 : Support python `3.9`,`3.10`. `Changelog <https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.2>`_
+10/15/2022 : Support python `3.9`,`3.10` . `Changelog <https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.2>`_
 
 06/11/2022 : Improve compatibility with tensorflow `2.x`. `Changelog <https://github.com/shenweichen/DeepCTR/releases/tag/v0.9.1>`_