Machine Learning & Natural Language Processing

The titles without a hyperlink are to be written, and would be updated soon 🙇🏻‍♂️

  • 🐷 = fundamental theories
  • 👨‍👩‍👧‍👦 = series of papers on a same topic
  • 🐶 = a single paper


1 Maths

1.1 Linear Algebra & Functional Analysis

1.2 Probability & Statistics

1.3 Optimization & Numerical Computation



2 ML

2.1 Fundamentals

2.2 Deep Clustering & Subspace Clustering

2.3 Spectral Methods & GNN

2.4 Few-shot Learning

– Data Augmentation

– Metric Learning

– Meta Optimizer Based

– Applications in NLP



3 NLP

3.1 Fundamentals

3.2 Information Extraction

– Sequence Labelling

– Neural Relation Extraction

– Relational Triple Extraction

– Event Extraction

3.3 Knowledge Graph

– Knowledge Representation Learning

– Entity Alignment



4 Others