Automated Machine Learning Lab

Metalearning and Automatic Model Recommendation Based on Knowledge-base

Publications List:

1. Automatic Machine Learning Derived from Scholarly Big Data

2. A Hybrid Approach for Automatic Model Recommendation

3. AutoGRD: Model Recommendation Through Graphical Dataset Representation

​

Meta-Features and Auto Feature Selection\Generation

Publications List:

1. ExploreKit: Automatic Feature Generation and Selection

​

Optimal Machine Learning Pipeline Search and Recommendation 

Publications List:

1. RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines

2. DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering

​

Explainability of the Models\Instances 

1. Explaining anomalies detected by autoencoders using SHAP

​

Neural Network Architecture Search 

1. Source Model Selection for Deep Learning in the Time Series Domain

2. A meta-learning Approach for Image Classification Architecture Recommendation

​

Additional Research Topics

1. Model Robustness (general and over time)

2. Data Augmentation

3. Learning on Budget

4. Model Compression