: Performance support is happening where we work and live. Under a tree and at a park bench, in a submarine, at a parent-teacher meeting, in a cubicle, or on the manufacturing floo...
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Correlations in traffic patterns are an important facet of the workloads faced by real systems, and one that has far-reaching consequences on the performance and optimization of t...
Varun Gupta, Michelle Burroughs, Mor Harchol-Balte...
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM ...
The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total...