/cooperative-competitive-learning

Potentially helpful methods for specialized ensemble learning.

Reading List

This repository collates the papers I am reading for my MSCS thesis.

2015 and later

Paper Method Venue Code
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss SNNL ICML 2019
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models MMVAE NeurIPS 2019 PyTorch
Multimodal Generative Models for Scalable Weakly-Supervised Learning MVAE NeurIPS 2018 PyTorch
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization SS AVTS NeurIPS 2018
Cooperative neural networks: Exploiting prior independence structure for improved classification CoNN NeurIPS 2018 PyTorch
Learning to Specialize with Knowledge Distillation for Visual Question Answering MCL-KD NeurIPS 2018 PyTorch
KATE: K-Competitive Autoencoder for Text KATE KDD 2017 Keras
Distilling the Knowledge in Neural Networks KD NeurIPS 2015 Workshop
A network of deep neural networks for distant speech recognition CN-DNN ICASSP 2017
Cooperative Training for Generative Modeling of Discrete Data CoT ICML 2019
Learning a Text-Video Embedding from Incomplete and Heterogeneous Data MEE PyTorch
MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings MIX'EM ACCV 2020
Confident Multiple Choice Learning CMCL ICML 2017 TensorFlow
Stochastic Multiple Choice Learning sMCL NeurIPS 2016

2014 and older

Paper Method Venue Code
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs MCL NeurIPS 2012
A Cooperative Ensemble Learning System CELS IJCNN 1998