Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Machine learning approaches to coreference resolution are typically supervised, and require expensive labeled data. Some unsupervised approaches have been proposed (e.g., Haghighi...
Reliable estimation of the classification performance of learned predictive models is difficult, when working in the small sample setting. When dealing with biological data it is ...
Antti Airola, Tapio Pahikkala, Willem Waegeman, Be...
This paper presents a simple and intuitive method for mining search engine query logs to get fast query recommendations on a large scale industrial-strength search engine. In orde...
Most cryptographic algorithms provide a means for secret and authentic communication. However, under many circumstances, the ability to repudiate messages or deny a conversation i...
Ian Goldberg, Berkant Ustaoglu, Matthew Van Gundy,...