Use Proper Baselines!
Unfortunately I suspect many researchers make their results looks better by using poor baselines. I give some thoughts on this, based on a recent discussion with a PhD student.
Tag: Machine Learning
Many Papers on Machine Learning in NLP are Scientifically Dubious
In response to a previous blog, many people expressed concerns to me about the quality of many papers they saw on ML in NLP. I summarise some of these concerns, which are worrying.
Learning does not require evaluation metrics
I was recently asked if machine learning requires evaluation metrics. The answer is no, and the fact that people are asking such questions suggests that some newcomers to the field may have a limited perspective on NLP research methodology.
Lexical Choice Needs Machine Learning!
Lexical choice is an area of NLG which really needs machine-learning and data-based techniques.
Notes from a Dev Conf: Sensible Attitude to Trendy AI Tech, Arria Presentations
I went to my first developers conference last week and was impressed, not least by the sensible attitude towards deep learning and other trendy AI technology.
Should I Use Deep Learning?
There is a lot of hype around deep learning. especially at business-oriented AI events. I suggest some questions to think about for companies who are considering using DL.
Embedding Machine Learning in a Rules-Based NLG System
I think we should use rules to make simple high-value decisions, and learning to make complex low-value decisions, within an architecture where ML decision makers are embedded in a rules-based framework.
