Online algorithms are designed to make decisions sequentially, without complete knowledge of future inputs. In many real-world applications—from scheduling and resource allocation to network ...

When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm's output matches reality.

Researchers at Carnegie Mellon University have developed a new system for detecting bias in otherwise opaque algorithms. In a paper presented today at the IEEE ...