We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
In multi-instance learning, the training examples are bags composed of instances without labels and the task is to predict the labels of unseen bags through analyzing the training...
Abstract— We investigate a widely popular Least-RecentlyUsed (LRU) cache replacement algorithm with semi-Markov modulated requests. Semi-Markov processes provide the flexibility...
We describe cache architecture, intended for prototype-oriented IC platforms, that automatically finds the best cache configuration for a particular application. The cache itself ...
The increase in high-performance microprocessor power consumption is due in part to the large power overhead of wideissue, highly speculative cores. Microarchitectural speculation...
Karthik Natarajan, Heather Hanson, Stephen W. Keck...