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This repository collects Multitask-Learning related materials, mainly including the homepage of representative scholars, papers, surveys, slides, proceedings, and open-source projects. Welcome to share these materials!

• Something New!!!
  • CS330: Deep Multi-Task and Meta-Learning
• Homepage
  • Rich Caruana's (terribly out-of-date) Home Page
  • Massimiliano Pontil - UCL
  • Jiayu Zhou | Machine Learning at Michigan State University
  • Yu Zhang (张宇) - HKUST
  • Tong Zhang (张潼)- Tencent AI Lab
  • Fuzhen Zhuang (庄福振)
  • Lei Han's Homepage
  • Pattern Recognition & Neural Computing Group - NUAA
  • Fei Sha University of Southern California
  • Dr Xiaojun Chang – Faculty of Information Technology – Monash University
  • Yu-Gang Jiang Prof.
  • Zhuoliang Kang Ph.D student, Computer Science, USC
  • Shiliang Sun’s Home Page
  • Dr. Timothy Hospedales
  • ML^2 @ UCF
  • Elisa Ricci
  • Gjorgji Strezoski
  • Machine Learning with Interdependent and Non-identically Distributed Data
  • SFU Machine Learning Reading Group
• Github
  • Logistic Regression
    • Multi-task logistic regression in brain-computer interfaces
  • Bayesian Methods
    • Kernelized Bayesian Multitask Learning
    • Parametric Bayesian multi-task learning for modeling biomarker trajectories
    • Bayesian Multitask Multiple Kernel Learning
  • Gaussian Process
    • Multi-task Gaussian process (MTGP)
    • Gaussian process multi-task learning
  • Sparse & Low Rank Methods
    • Asymmetric Multi-Task Learning
    • Hierarchical_Multi_Task_Learning
    • Asynchronous Multi-Task Learning
    • HMTL: Hierarchical Multi-Task Learning
    • Multi-task feature learning
    • Multiplicative MultiTask Feature Learning (MMTFL)
    • Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
    • Variable Selection and Task Grouping for Multi-Task Learning (VSTG-MTL)
    • Calibrated Multi-Task Learning Based on Non-convex Low Rank
    • Multi-task_Survival_Analysis
    • A Multi-Task Learning Formulation for Survival Analysis
  • Federated Multi-Task Learning
  • Online Learning
    • Online Multi-Task Learning Toolkit (OMT) v1.0
  • Reinforcement Learning
    • Robust-Multitask-Reinforcement Learning
  • Package & Toolbox
    • MALSAR: Multi-task learning via Structural Regularization
    • MALSAR package Version 1.1
    • Multi Task Learning Package for Matlab
    • Regularized Multi-task Learning in R
    • Package to apply MTL on a few dataset
    • Matlab MultiClass MultiTask Learning (MCMTL) toolbox
    • Personalized Multitask Learning
• Papers
  • Multitask Learning
  • An overview of multi-task learning
  • A brief review on multi-task learning
  • A review on multi-task metric learning
  • Safe sample screening for regularized multi-task learning
  • Multi-task feature learning by using trace norm regularization
  • Multi-Task Clustering with Model Relation Learning
  • Online Multitask Learning
  • Online multitask relative similarity learning
  • New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks
  • Manifold Regularized Multi-Task Learning
  • Multi-Objective Multi-Task Learning
  • Multi-Task Active Learning
• Arxiv
  • A Survey on Multi-Task Learning
  • Self-Paced Multi-Task Clustering
  • Model-Protected Multi-Task Learning
• Slides
  • Article slides
    • Multi-Task Feature Learning
    • Multi-Stage Multi-Task Feature Learning
    • A Dirty Model for Multitask Learning
    • Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
    • A Graph-based Framework for Multi-Task Multi-View Learning
  • Lecture slides
    • Multi-Task Learning: The Bayesian Way, 2006
    • Multi-task Gaussian Process Prediction, 2008
    • Multitask Multiple Kernel Learning, 2010
    • Multi-task Regularization of Generative Similarity Models, 2011
    • Learning Multiple Tasks with a Sparse Matrix-Normal Penalty, 2011
    • Multi-Task Learning via Matrix Regularization
    • Multi-Task Learning: Theory, Algorithms, and Applications, 2012
    • Multi-task and Transfer Learning, 2013
    • Multi-task Learning and Structured Sparsity, 2013
    • Multi-task Learning, 2013
    • Multi-task Learning, 2014
    • Multi-Task Learning: Models, Optimization and Applications, 2016
    • Domain Adaptation / Multi-Task Learning Methods and Examples
    • Recent Advances in Multi-Task Learning
• Resources
  • Task Sensitive Feature Exploration and Learning for Multi-Task Graph Classification
  • BMTMKL: Bayesian Multitask Multiple Kernel Learning
  • Multitask Learning / Domain Adaptation
  • Multitask Kernel Methods
  • Multitask Deep Learning
• Package & Toolbox
  • RMTL: Regularized Multi-Task Learning
  • Multi-Task Learning: Theory, Algorithms, and Applications
  • An Tutorial for Regularized Multi-task Learning using the package RMTL
  • SparseMTL Toolbox
  • Probabilistic Machine Learning

• Multi-Label Learning
  • KEEL-dataset repository
• Few-Shot Learning & Meta-Learning
  • PyTorch Meta-learning Framework for Researchers
  • Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
  • Awesome Meta Learning
  • awesome-meta-learning
  • Torchmeta
  • Model-Agnostic Meta-Learning
• Federated Learning
  • Federated Learning
  • Awesome Federated Learning
  • Awesome Federated Computing

• EE364a: Convex Optimization I Professor Stephen Boyd, Stanford University
• EE227BT: Convex Optimization — Fall 2013
• CRAN - Package ADMM
• Proximal-Proximal-Gradient Method
• Proximal gradient method