Machine learning research often has a large experimental component. While the experimental methodology employed in machine learning has improved much over the years, repeatability ...
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
Indian organisations have transformed organisational learning to face multiple challenges posed by external market conditions, legal and regulatory considerations and internal fact...
Evidence theory has been widely applied to uncertain reasoning. However, the evidence space and hypothesis space are each defined as a fixed set. If the theory is applied to solve...
Qingxiang Wu, Xi Huang, David A. Bell, Guilin Qi, ...
Most process models calibrate their internal settings using historical data. Collecting this data is expensive, tedious, and often an incomplete process. Is it possible to make acc...
Tim Menzies, Oussama El-Rawas, Barry W. Boehm, Ray...