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» Scalable, updatable predictive models for sequence data
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ACL
2012
11 years 11 months ago
Automatic Event Extraction with Structured Preference Modeling
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
Wei Lu, Dan Roth
SIGMOD
2004
ACM
173views Database» more  SIGMOD 2004»
14 years 9 months ago
Relaxed Currency and Consistency: How to Say "Good Enough" in SQL
Despite the widespread and growing use of asynchronous copies to improve scalability, performance and availability, this practice still lacks a firm semantic foundation. Applicati...
Hongfei Guo, Jonathan Goldstein, Per-Åke Lar...
CAIP
2007
Springer
152views Image Analysis» more  CAIP 2007»
14 years 3 months ago
Adaptable Model-Based Tracking Using Analysis-by-Synthesis Techniques
Abstract. In this paper we present a novel analysis-by-synthesis approach for real-time camera tracking in industrial scenarios. The camera pose estimation is based on the tracking...
Harald Wuest, Folker Wientapper, Didier Stricker
AROBOTS
2011
13 years 4 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
NIPS
2001
13 years 10 months ago
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
Yun Gao, Michael J. Black, Elie Bienenstock, Shy S...