منابع مشابه
A Little Learning.
Follow up what we will offer in this article about a little learning. You know really that this book is coming as the best seller book today. So, when you are really a good reader or you're fans of the author, it does will be funny if you don't have this book. It means that you have to get this book. For you who are starting to learn about something new and feel curious about this book, it's ea...
متن کاملA little learning is a dang'rous thing.
The Batten Briefings is a quarterly discussion of innovation, entrepreneurship, and corporate transformation. We invite you to participate. To contribute to the discussion by commenting on previous articles or suggesting topics for future ones, or for copies of previous issues, please write to the editor in chief. The Batten Institute invests in applied research and knowledge transfer programs ...
متن کاملLearning Rotations Learning rotations with little regret
We describe online algorithms for learning a rotation from pairs of unit vectors in R. We show that the expected regret of our online algorithm compared to the best fixed rotation chosen offline over T iterations is O( √ nT ). We also give a lower bound that proves that this expected regret bound is optimal within a constant factor. This resolves an open problem posed in COLT 2008. Our online a...
متن کاملBig Learning with Little RAM
In large-scale machine learning, available memory (RAM) is often a key constraint, both during model training and when making new predictions. In this paper, we reduce memory cost by projecting our weight vector β ∈ R onto a coarse discrete set using randomized rounding. Because the values of the discrete set can be stored more compactly than standard 32-bit float encodings, this reduces RAM us...
متن کاملLearning from Little: Comparison of Classifiers Given Little Training
Many real-world machine learning tasks are faced with the problem of small training sets. Additionally, the class distribution of the training set often does not match the target distribution. In this paper we compare the performance of many learning models on a substantial benchmark of binary text classification tasks having small training sets. We vary the training size and class distribution...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: British Journal of Anaesthesia
سال: 1973
ISSN: 0007-0912
DOI: 10.1093/bja/45.7.764