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ACL
2009
15 years 5 months ago
Distributional Representations for Handling Sparsity in Supervised Sequence-Labeling
Supervised sequence-labeling systems in natural language processing often suffer from data sparsity because they use word types as features in their prediction tasks. Consequently...
Fei Huang, Alexander Yates
ACL
2006
15 years 8 months ago
URES : an Unsupervised Web Relation Extraction System
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these a...
Binyamin Rosenfeld, Ronen Feldman
EMNLP
2011
14 years 6 months ago
Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
SCALESPACE
2007
Springer
16 years 1 months ago
Non-negative Sparse Modeling of Textures
This paper presents a statistical model for textures that uses a non-negative decomposition on a set of local atoms learned from an exemplar. This model is described by the varianc...
Gabriel Peyré
SIGUCCS
2006
ACM
16 years 1 months ago
Better results in mathematics lessons with a virtual personal teacher
In this paper we present the results of an experiment made with our e-librarian service ”MatES”, an e-Learning tool on fractions in mathematics. MatES allows students to enter...
Serge Linckels, Carole Dording, Christoph Meinel