Upcoming ECML talks

June 18th, 2013

I was just notified that two of my papers got accepted for presentation at the European Conference on Machine Learning (ECML). This is great news and I am looking forward to the conference and the opportunity to share my results and get some valuable feedback.

The regular paper that got accepted is titled “Hub Co-occurrence Modeling for Robust High-dimensional kNN Classification” and has to do with learning from the second-order neighbor dependencies (co-occurrences) in intrinsically high-dimensional data. We have analyzed the consequences of hubness for the neighbor co-occurrence distributions and utilized them in a novel kNN classification method, the Augmented Naive Hubness-Bayesian k-NN (ANHBNN). The method is based on the Hidden Naive Bayes model and introduces hidden nodes in order to model dependencies between individual attributes. The attributes of the model are the neighbor occurrences themselves. This paper solves some problems but also raises new issues and it shows how difficult and multi-faceted the hubness issue can become.

The other paper that got accepted is actually a demo-paper on the Image Hub Explorer tool, which means that I will get the opportunity to present my software at the conference and demonstrate its capabilities in front of the gathered audience. I am really happy about this and I am certain that it will be a great experience. The demo paper is titled: Image Hub Explorer: Evaluating Representations and Metrics for Content-based Image Retrieval and Object Recognition.

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