It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...

Computer science is an ever-evolving field that impacts almost every aspect of our daily lives, yet understanding how its ...

1981 — Gerald Dejong introduces the concept of Explanation Based Learning (EBL), in which a computer analyses training data and creates a general rule it can follow by discarding unimportant data.

Learning algorithms already make a lot of important decisions every day, from who gets credit to who gets interviewed for a job to who gets flagged as a potential terrorist. And they make mistakes.

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...

The labeled data is fed to computer algorithms, teaching the algorithms what to look for. After ingesting millions of labeled images, the algorithms become expert at recognizing what they have ...

Machine Learning is the study of algorithms that improve automatically through experience. Topics covered typically include Bayesian Learning, Decision Trees, Genetic Algorithms, Neural Networks. This ...

COMP_SCI 497: Learning Augmented Online Algorithms VIEW ALL COURSE TIMES AND SESSIONS Prerequisites CS 336 or Any PhD student Description In applications like routing, job scheduling, caching, etc., ...

Blockchain technologies are digital systems that work by distributing copies of information across several computers, also ...