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praxai:start [2022/10/24 12:24] – [Program] sbk | praxai:start [2023/04/14 07:04] – [Important Dates] sbk | ||
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**PRAXAI webpage address is [[http:// | **PRAXAI webpage address is [[http:// | ||
- | PRAXAI | + | PRAXAI |
Conference on Data Science and Advanced Analytics]] focuses on bringing the research on Explainable | Conference on Data Science and Advanced Analytics]] focuses on bringing the research on Explainable | ||
Artificial Intelligence (XAI) to actual applications and tools that help | Artificial Intelligence (XAI) to actual applications and tools that help | ||
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daily work. | daily work. | ||
- | The PRAXAI | + | The PRAXAI |
===== Important Dates ===== | ===== Important Dates ===== | ||
- | * **Submission Deadline**: <del>June 1, 2022</ | + | * **Submission Deadline**: <del>May 2</ |
- | * **Notification**: | + | * **Notification**: |
- | * **Camera Ready Due**: <del>August | + | * **Camera Ready Due**: August |
+ | * **Conference date**: October 9-13 | ||
===== Call for papers ===== | ===== Call for papers ===== | ||
- | * {{ : | + | * {{ : |
- | ===== Program ===== | ||
- | Zoom Link: [[https:// | ||
- | PRAXAI Session A: 14:00-15:20 (CET) Session Chair: dr Szymon Bobek: | ||
- | - **Fast Hybrid Oracle-Explainer Approach to Explainability Using Optimized Search of Comprehensible Decision Trees** \\ // | ||
- | - Video: [[https:// | ||
- | - **SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP** \\ // | ||
- | - Video: [[https:// | ||
- | - **Abstract Argumentation for Explainable Satellite Scheduling** \\ //Powell, Cheyenne; Riccardi, Annalisa// | ||
- | - Wideo: [[https:// | ||
- | - **Explaining Human Activities Instances Using Deep Learning Classifiers** \\ //Arrotta, Luca; Civitarese, Gabriele; Fiori, Michele; Bettini, Claudio// | ||
- | - Wideo: [[https:// | ||
- | |||
- | Break (10 minutes) | ||
- | |||
- | PRAXAI Session B: 15:30-16:50 (CET) Session Chair: dr Victor Victor Rodriguez-Fernandez: | ||
- | - **Explainable expected goal models for performance analysis in football analytics** \\ //Cavus, Mustafa; Biecek, Przemyslaw// | ||
- | - Wideo: [[https:// | ||
- | - **Why is the prediction wrong? Towards underfitting case explanation via meta-classification** \\ //ZHOU, Sheng; BLANCHART, Pierre; Crucianu, Michel; Ferecatu, Marin// | ||
- | - **Streamlining models with explanations in the learning loop** \\ //Lomuscio, Francesco; Bajardi, Paolo; Perotti, Alan; Amparore, Elvio// | ||
- | - **Roll Wear Prediction in Strip Cold Rolling with Physics-Informed Autoencoder and Counterfactual Explanations** \\ // | ||
- | - Video: [[https:// | ||
===== Submission Instructions ===== | ===== Submission Instructions ===== | ||
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Authors are also encouraged to submit supplementary materials, i.e., providing the source code and data through a GitHub-like public repository to support the reproducibility of their research results. | Authors are also encouraged to submit supplementary materials, i.e., providing the source code and data through a GitHub-like public repository to support the reproducibility of their research results. | ||
- | Electronic submission site: https://cmt3.research.microsoft.com/DSAA2022 | + | Electronic submission site: [[https://easychair.org/my/conference? |
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===== Topics of interest ===== | ===== Topics of interest ===== | ||
+ | * Industry 4.0/5.0 and XAI | ||
* Model explanations verbalized in human-comprehensible natural language | * Model explanations verbalized in human-comprehensible natural language | ||
* Explainable Reinforcement learning | * Explainable Reinforcement learning | ||
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* Visualization of model explanations for different types of data apart from language and images (tabular data, time series, graphs, etc.) | * Visualization of model explanations for different types of data apart from language and images (tabular data, time series, graphs, etc.) | ||
* XAI software development and its integration into popular ML/DL libraries | * XAI software development and its integration into popular ML/DL libraries | ||
+ | * Fairness and XAI | ||
+ | * Ethics and XAI | ||
+ | * Trust in XAI systems | ||
+ | * XAI in real-world applications: | ||
+ | |||
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- | ===== Papers ===== | ||
- | * Fast Hybrid Oracle-Explainer Approach to Explainability Using Optimized Search of Comprehensible Decision Trees \\ Szczepanski, | ||
- | * SurvSHAP: A Proxy-Based Algorithm for Explaining Survival Models with SHAP \\ Alabdallah, Abdallah; Pashami, Sepideh; Rognvaldsson, | ||
- | * Abstract Argumentation for Explainable Satellite Scheduling \\ Powell, Cheyenne; Riccardi, Annalisa | ||
- | * Explaining Human Activities Instances Using Deep Learning Classifiers \\ Arrotta, Luca; Civitarese, Gabriele; Fiori, Michele; Bettini, Claudio | ||
- | * Explainable expected goal models for performance analysis in football analytics \\ Cavus, Mustafa; Biecek, Przemyslaw | ||
- | * Why is the prediction wrong? Towards underfitting case explanation via meta-classification \\ ZHOU, Sheng; BLANCHART, Pierre; Crucianu, Michel; Ferecatu, Marin | ||
- | * Streamlining models with explanations in the learning loop \\ Lomuscio, Francesco; Bajardi, Paolo; Perotti, Alan; Amparore, Elvio | ||
- | * Roll Wear Prediction in Strip Cold Rolling with Physics-Informed Autoencoder and Counterfactual Explanations \\ Jakubowski, Jakub; Stanisz, Przemysław; | ||
===== Past events ===== | ===== Past events ===== | ||
* [[praxai: | * [[praxai: | ||
+ | * [[praxai: | ||