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» Learning from Multiple Sources of Inaccurate Data
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ICCV
2003
IEEE
16 years 5 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann
ACL
2010
15 years 1 months ago
Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
One of the main obstacles to producing high quality joint models is the lack of jointly annotated data. Joint modeling of multiple natural language processing tasks outperforms si...
Jenny Rose Finkel, Christopher D. Manning
138
Voted
BTW
2009
Springer
132views Database» more  BTW 2009»
15 years 8 months ago
A Bayesian Approach to Estimating the Selectivity of Conjunctive Predicates
: Cost-based optimizers in relational databases make use of data statistics to estimate intermediate result cardinalities. Those cardinalities are needed to estimate access plan co...
M. Heimel, Volker Markl, Keshava Murthy
144
Voted
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
15 years 8 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diļ...
Xiao Zhang, Prasenjit Mitra
142
Voted
DAWAK
2005
Springer
15 years 9 months ago
Graph-Based Modeling of ETL Activities with Multi-level Transformations and Updates
Extract-Transform-Load (ETL) workflows are data centric workflows responsible for transferring, cleaning, and loading data from their respective sources to the warehouse. Previous ...
Alkis Simitsis, Panos Vassiliadis, Manolis Terrovi...