Section 4.22.1.0.1.1 - Part 1 - Wikipedia - Transfer Learning

Section 4.22.1.0.1.2 - Part 2 - Ruder - Transfer Learning, Machine Learning's Next Frontier

Section 4.22.1.0.1.3 - Part 3 - Sarkar - A Comprehensive Hands-on Guide to Transfer Learning

Section 4.22.1.0.1.4 - Part 4 - Papers wtih Code - Transfer Learning

Section 4.22.1.0.2.1 - Part 1 - Torrey,Shavlik - Transfer Learning

Section 4.22.1.0.2.2 - Part 2 - Weiss,Khoshgoftaar,Wang - A Survey of Transfer Learning

Section 4.22.1.0.2.3 - Part 3 - Tan,Sun,Kong,Zhang,Yang,Liu - A Survey on Deep Transfer Learning

Section 4.22.1.0.2.4 - Part 4 - Yosinki,Clne,Bengio,Lipson - How transferrable are features in deep neural networks

Section 4.22.2.0.1.1 - Part 1 - Wikipedia - Multi-Task Learning

Section 4.22.2.0.1.2 - Part 2 - Ruder - Multi-Task Learning

Section 4.22.2.0.1.3 - Part 3 - Honchar - Multi-Task Learning: Teach your AI more to make it better

Section 4.22.2.0.1.4 - Part 4 - Ratner,Hancock,Ré - Emerging Topic in Multi-Task Learning Systems

Section 4.22.2.0.2.1 - Part 1 - Zhang,Yang - A Survey on Multi-Task Learning

Section 4.22.2.0.2.2 - Part 2 - Caruana - A Survey on Multi-Task Learning

Section 4.22.2.0.2.3 - Part 3 - Meyerson,Miikkulainen - Beyond Shared Hierachies: Deep Multi-task Learning through Soft Layer Ordering

Section 4.22.2.0.2.4 - Part 4 - Ruder - An Overview of Multi-Task Learning in Deep Neural Networks

Section 4.22.2.0.2.5 - Part 5 - Sener,Koltun - Multi-Task Learning as Multi-Objective Optimization

Section 4.22.2.0.2.6 - Part 6 - Clark,Luon,Khandelwal,Manning,Le - BAM! Born-Again Multi-Task Networks for NLP

Section 4.22.2.0.2.7 - Part 7 - Fang,Ma,Zhang,Zhang,Bai - Dynamic Multi-Task Learning with CNN's

Section 4.22.3.0.1.1 - Part 1 - Wolf - From Zero to Research - An introduction to Meta Learning

Section 4.22.3.0.1.2 - Part 2 - Wikipedia - Meta Learning

Section 4.22.3.0.1.3 - Part 3 - Scholarpedia - Meta Learning

Section 4.22.3.0.1.4 - Part 4 - Joglekar - Understanding Few-Shot Intelligence as a Meta Learning problem

Section 4.22.3.0.2.1 - Part 1 - Weng - Meta Learning

Section 4.22.3.0.2.2 - Part 2 - Finn,Rajeswaran,Kakade,Levine - Meta Learning

Section 4.22.3.0.2.3 - Part 3 - Finn,Levine - Probablistic Model-Agnostic Meta Learning

Section 4.22.3.0.2.4 - Part 4 - Vlialta,Carrier,Brazdil - Meta Learning: Concepts and Techniques

Section 4.22.4.0.1.1 - Part 1 - Lomonaco - Summary of the 2nd Continual Learning Workshop at NIPS 2018

Section 4.22.4.0.1.2 - Part 2 - Lomonaco - Articles on Continual AI

Section 4.22.4.0.2.1 - Part 1 - Ven,Tolias - Three scenarios for continual learning

Section 4.22.4.0.2.2 - Part 2 - Parisi,Kemker,Part,Kanan,Wermter - Continual Lifelong Learning with Neural Networks: A Review

Section 4.22.4.0.2.3 - Part 3 - Ring - Toward a Formal Framework for Continual Learning

Section 4.22.4.0.2.4 - Part 4 - Chen,Liu - Lifelong Machine Learning: Continual Learning and Catastrophic Forgetting

Section 4.22.5.0.1.1 - One Shot

Section 4.22.5.0.1.2 - Few Shot

Section 4.22.5.0.2.1 - Zero Shot

Section 4.22.5.0.2.2 - One Shot

Section 4.22.5.0.2.3 - Few Shot

Section 4.22.6.0.2.1 - Part 1 - Castro,Jimenez,Guil,Schmid,Alahari - End-to_end Incremental Learning

Section 4.22.6.0.2.2 - Part 2 - Losing,Hammer,Wersing - Incremental Online Learning: A Review and Comparison of the State of the Art Algorithms

Section 4.22.6.0.2.3 - Part 3 - Bouchachia,Vanaret - Incremental Learning Based on Growing Gaussian Mixture Models

Section 4.22.6.0.2.4 - Part 4 - Liu,Chen - Incremental batch learning with support vector machines

Section 4.22.6.0.2.5 - Part 5 - Ruping - Incremental Learning with Support Vector Machiness

Section 4.22.6.0.2.6 - Part 6 - Muhlbaier,Topalis,Polikar - Learn++.MT: A New Approach to Incremental Learning

Section 4.22.6.0.2.7 - Part 7 - Ralaivola,Alche-Buc - Incremental support vector machine learning: A local approach

Section 4.22.6.0.2.8 - Part 8 - Gepperth,Hammer - Incremental learning algorithms and applications

Section 4.22.7.0.1.1 - Part 1 - AutoML.org - Automl

Section 4.22.7.0.1.2 - Part 2 - Wikipedia - Automated Machine Learning

Section 4.22.7.0.1.3 - Part 3 - MLJAR - Automated Machine Learning Software List

Section 4.22.7.0.1.4 - Part 4 - OpenML - Automated Machine Learning Benchmark

Section 4.22.7.0.2.1 - Part 1 - Zoph,Vasudevan,Shlens,Le - Learning Transferable Architectures for Scalable Image Recognition

Section 4.22.7.0.2.2 - Part 2 - He,Zhao,Chu - AutoML: A Survey of the State-of-the-Art

Section 4.22.7.0.2.3 - Part 3 - Feurer,Klein,Eggensperger,Springenberg,Blum,Hutter - Efficient and Robust Automated Machine Learning

Section 4.22.7.0.2.4 - Part 4 - AutoML.org - Automated Machine Learning: Methods, Systems, Challenges

Section 4.22.7.0.2.5 - Part 5 - HiBayesian - Awesome AutoML Papers

Section 4.22.0.1.1 - Wikipedia - Neuroplasticity

Section 4.22.0.2.1 - Allam - Achieving Neuroplasticity in ANNs through Smart Cities

Section 4.22.0.2.2 - Perwej,Perwej - A Neuroplasticity (Brain Plasticity) approach in use in ANN

Section 4.22.0.2.3 - Miconi,Clune,Stanley - Differentiable plasticity: training plastic neural networks with backpropagation