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» Scalable, updatable predictive models for sequence data
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ACL
2012
13 years 6 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»
16 years 4 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»
15 years 10 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
14 years 11 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
15 years 5 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...