This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we also present a large number of f...
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...
User feedback has proven very successful to query large multimedia databases. Due to the nature of the data representation and the mismatch between mathematical models and human p...
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...