We propose and evaluate a probabilistic framework for estimating a Twitter user’s city-level location based purely on the content of the user’s tweets, even in the absence of ...
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
We study the problem of aggregating data from a sparse set of nodes in a wireless sensor network. This is a common situation when a sensor network is deployed to detect relatively...
Jie Gao, Leonidas J. Guibas, Nikola Milosavljevic,...
A frequently arising problem in computational geometry is when a physical structure, such as an ad-hoc wireless sensor network or a protein backbone, can measure local information...
Mihai Badoiu, Erik D. Demaine, Mohammad Taghi Haji...