Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
Abstract-- We propose a new method for automatically accessing an internet database of 3D models that are searchable only by their user-annotated labels, for using them for vision ...
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
We propose and study a new ranking problem in versioned databases. Consider a database of versioned objects which have different valid instances along a history (e.g., documents i...
Leong Hou U, Nikos Mamoulis, Klaus Berberich, Srik...
In this paper, we present an event parsing algorithm based on Stochastic Context Sensitive Grammar (SCSG) for understanding events, inferring the goal of agents, and predicting th...
Mingtao Pei, School of Computer Science, Yunde Jia...