Awesome Knowledge Distillation

Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling

This is the public repository of EMNLP 2023 paper "DisCo: Co-training Distilled Student Models for Semi-supervised Text Mining"

[Nature Machine Intelligence Journal] Official pytorch implementation for Uncertainty-Guided Dual-Views for Semi-Supervised Volumetric Medical Image Segmentation

[MICCAI2021] This is an official PyTorch implementation for "Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation"

Code and model for "Multi-dataset Training of Transformers for Robust Action Recognition", NeurIPS 2022 Spotlight

This repository holds the implementation, for the thesis project: Improving Collaborative Filtering Techniques by the use of Co-Training in Recommender Systems. This project was done under a thesis research for Fernando Benjamín Pérez Maurera, under supervision of Professor Paolo Cremonesi and Engineer Maurizio Ferrari, at Politecnico di Milano.

Official Code for our Findings of ACL 2022 paper: Co-training an Unsupervised Constituency Parser with Weak Supervision

Audio Classification Kaggle

Co-training GNN framework

Data analytics project in R to create a predictive model for the detection of objectivity in sports articles, based on co-training.

Large-scale semi-supervised annotation (self-learning, co-training) for text (code for papers @ KDD17, @ KAIS19); Repository maintained by Vasileios Iosifidis.

Semi-supervised learning techniques (pseudo-label, mixmatch, and co-training) for pre-trained BERT language model amidst low-data regime based on molecular SMILES from the Molecule Net benchmark.

Semisupervised classification methods (SSC) with Spark-ML, study and implementation

end of 2nd year of engineering project