Online auction Web sites are fast changing, highly dynamic, and complex as they involve tremendous sellers and potential buyers, as well as a huge amount of items listed for biddi...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
We apply speculative multithreading to sequential Java programs in software to achieve speedup on existing multiprocessors. A common speculation library supports both Java bytecod...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages:...