transfer learning Neural Transfer Learning for Natural Language Processing (PhD thesis) This post discusses my PhD thesis Neural Transfer Learning for Natural Language Processing and some new material presented in it.
transfer learning 10 Exciting Ideas of 2018 in NLP This post gathers 10 ideas that I found exciting and impactful this year—and that we'll likely see more of in the future. For each idea, it highlights 1-2 papers that execute them well.
language models A Review of the Neural History of Natural Language Processing This post expands on the Frontiers of Natural Language Processing session organized at the Deep Learning Indaba 2018. It discusses major recent advances in NLP focusing on neural network-based methods.
transfer learning Requests for Research It can be hard to find compelling topics to work on and know what questions to ask when you are just starting as a researcher. This post aims to provide inspiration and ideas for research directions to junior researchers and those trying to get into research.
multi-task learning Multi-Task Learning Objectives for Natural Language Processing Multi-task learning is becoming increasingly popular in NLP but it is still not understood very well which tasks are useful. As inspiration, this post gives an overview of the most common auxiliary tasks used for multi-task learning for NLP.
multi-task learning An Overview of Multi-Task Learning in Deep Neural Networks Multi-task learning is becoming more and more popular. This post gives a general overview of the current state of multi-task learning. In particular, it provides context for current neural network-based methods by discussing the extensive multi-task learning literature.
