Bellairs workshop 2013

2013 Bellairs Workshop on Machine Learning and Statistical Signal Processing for Data on Graphs

This workshop brought together leading international researchers who are developing and using machine learning and statistical signal processing methods to analyze data recorded on graphs and networks. The workshop consisted of research presentations and several tutorials. We discussed open problems and forged research collaborations, identifying promising future directions for graph data analysis. The event was held at McGill's beautiful Bellairs Research Institute in Holetown, Saint James Parish, Barbados.

Technical Program:

Full Presentations:

• Waheed Bajwa (Rutgers, USA), New Geometric Insights Into High-Dimensional Model Selection Using Marginal Correlations
• Petar Djuric (Stony Brook, USA), Distributed Sequential Estimation in a Network of Cooperative Agents
• Carlo Fischione (KTH, Sweden), Fast Lipschitz Optimization
• Jarvis Haupt (U Minnesota, USA), Adaptive Compressive Imaging Using Sparse Hierarchical Learned Dictionaries
• Mike Rabbat (McGill, Canada, workshop organizer), Consensus-Based Distributed Optimization: Communication/Computation Tradeoffs
• Alejandro Ribeiro (U Penn, USA), Hierarchical Clustering in Asymmetric Networks
• Anand Sarwate (TTI-C, USA), Differential Privacy in Machine Learning and Signal Processing
• Shreyas Sundaram (U Waterloo, Canada), Robustness of Complex Networks with Implications for Consensus and Contagion
• Chathuranga Weeraddana (KTH, Sweden), Multicell MISO Downlink Weighted Sum-Rate Minimization: A Distributed Approach

Short Presentations

• Sean Lawlor (McGill, Canada), Detecting Convoys in Asymmetric Networks
• Yunpeng Li (McGill, Canada), Statistical Modeling in RF Tomographic Tracking Using Received Signal Strength Measurements
• Shohreh Shaghaghian (McGill, Canada)
• Jun Ye Yu (McGill, Canada) Performance Comparison Between Collection Tree Protocol and Broadcast Gossip