Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
The Internet makes it possible to share and manipulate a vast quantity of information efficiently and effectively, but the rapid and chaotic growth experienced by the Net has gener...
We propose a framework for searching the Wikipedia with contextual information. Our framework extends the typical keyword search, by considering queries of the type q, p , where q...
Antti Ukkonen, Carlos Castillo, Debora Donato, Ari...
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...