We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Abstract. This paper describes an efficient method to construct reliable machine learning applications in peer-to-peer (P2P) networks by building ensemble based meta methods. We co...
Statistical approaches for building non-rigid deformable
models, such as the Active Appearance Model (AAM), have
enjoyed great popularity in recent years, but typically require
...
Akshay Asthana (Australian National University), R...
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes