We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
Motivated by structural properties of the Web graph that support efficient data structures for in memory adjacency queries, we study the extent to which a large network can be com...
Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, ...
—Probabilistic topic models were originally developed and utilised for document modeling and topic extraction in Information Retrieval. In this paper we describe a new approach f...
In recent years, both hashing-based similarity search and multimodal similarity search have aroused much research interest in the data mining and other communities. While hashing-...
Wide-area distributed applications are challenging to debug, optimize, and maintain. We present Wide-Area Project 5 (WAP5), which aims to make these tasks easier by exposing the c...
Patrick Reynolds, Janet L. Wiener, Jeffrey C. Mogu...