Reinforcement Learning for Capacity Tuning of Multi-Core Servers
Liat Ein-Dor*, Yossi Itach*, Aharon Bar-Hillel*, Amir Di-Nur+, and Ran Gilad-Bachrach*
*Intel Research Israel Labs and +Intel IT

Melody - Expert-Free System Analysis
Sivan Sabato, Elad Yom-Tov, and Ohad Rodeh
IBM Haifa Research Labs

Online Learning with Constraints for Systems
Branislav Kveton*, Jia Yuan Yu+, Georgios Theocharous*, and Shie Mannor+
*Intel Research and +McGill University

Reinforcement Learning for Utility-Based Grid Scheduling
Julien Perez, Balazs Kegl, and Cecile Germain-Renaud
University of Paris-Sud

Learning to Dynamically Allocate Memory
Nicolo Cesa-Bianchi* and Ofer Dekel+
*Universtia delgi Studi di Milano and +Microsoft Research

Software Unit Test Prioritization: A Statistical Approach
Jason V. Davis and Emmet Witchel
University of Texas at Austin

Using Machine Learning to Discover Service and Host Dependencies in Networked Systems
Paul Barham, Richard Black, Moises Goldszmidt, Rebecca Isaacs, John MacCormick, Richard Mortier, and Aleksandr Simma
Microsoft Research

Real-Time Anomaly Detection in Software Appliances
F. Knorn, D.J. Leith, and R.N. Shorten
Hamilton Institute, Ireland

Policy Search Optimization for Spatial Path Planning
Matthew E. Taylor, Katherine E. Coons, Behnam Robatmili, Doug Burger, and Kathryn S. McKinley
University of Texas at Austin

Dynamic Clustering of Interference Domains in Large Scale 802.11 Networks
Reza Lotun, Kan, Cai, and Mike Feeley
University of British Columbia

Network Planning Using Reinforcement Learning
Eric Vigeant, Shie Mannor, and Doina Precup
McGill University

Approaches to Anomaly Detection using Host Network-Traffic Traces
John Mark Agosta, Jaideep Chardrashekar, Frederic Giroire, Carl Livadas, and Jing Xu
Intel Research

Approximate Decision Making in Large-Scale Distributed Systems
Ling Huang*, Minos Garofalakis+, Anthony D. Joseph#, and Nina Taft*
*Intel Research, +Yahoo! Research, and #UC Berkeley

Tracking Malicious Regions of the IP Space
Avrim Blum*, Subhabrata Sen+, Oliver Spatscheck+, Dawn Song*, and Shobha Venkataraman*
*Carnegie Mellon University and +AT&T Labs Research

Response-Time Modeling for Resource Allocation and Energy-Informed SLAs
Peter Bodik, Charles Sutton, Armando Fox, David Patterson, and Michael Jordan
UC Berkeley

Discovering the Runtime Structure of Software with Probabilistic Generative Models
Scott Richardson, Michael Otte, Michael c. Mozer, Amer Diwan, Dan Connors
University of Colorado

Learning Link Quality in Wireless Communication Networks
Joseph E. Gonzalez, Andreas Krause, Katherine Chen, and Carlos Guestrin
Carnegie Mellon University