Learning Hidden Computational Processes Csml Talks Lecture #1
نویسنده
چکیده
There are lots of prediction tasks: what animal is this, when was the last time Greece held the Summer Olympics, what is the correct move to play in a game of Go? Machine learning has been quite successful in easier tasks: I am more interested in tasks like question answering, game playing, and theorem proving. For instance, consider a question-answering dataset: WikiTableQuestions (2108 tables, 22033 questions). More difficult than freebase, and the tables in the test data are not seen during training. Liang’s group created this dataset by crowd-sourcing. We are pretty happy with this set as a challenge problem in NLP. Of course this number is very small compared to ImageNet (1.2 million). If you can actually do this well after training on a small amount of data. As a baseline, you define some features and then try to rank the cells (information retrival) which only does 12.7%. Our method is better (37.1%) but it’s not 99%.
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