We propose a novel context sensitive algorithm for evaluation of ordinal attributes which exploits the information hidden in ordering of attributes’ and class’ values and prov...
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
Gossip protocols provide probabilistic reliability and scalability, but their inherent randomness may lead to high variation in number of messages that are received at different n...
Jay A. Patel, Indranil Gupta, Noshir S. Contractor
In this paper we address the problem of detecting topics in large-scale linked document collections. Recently, topic detection has become a very active area of research due to its...
Our participation in TREC 2003 aims to adapt the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) to the robust track and the topic distillation task o...
Giambattista Amati, Claudio Carpineto, Giovanni Ro...