Random Sampling
Related Papers
An Empirical Study of Active Learning with Support Vector Machines forJapanese Word Segmentation
We explore how active learning with Sup- port Vector Machines works well for a non-trivial task in natural language pro- cessing. We use Japanese word segmenta- tion as a test …...
Ensemble-based Active Learning for Parse Selection
Supervised estimation methods are widely seen as being superior to semi and fully unsuper- vised methods. However, supervised methods crucially rely upon training sets that need to be manually annotated. …...
Instance Sampling Methods for Pronoun Resolution
Instance sampling is a method to balance ex- tremely skewed training sets as they occur, for example, in machine learning settings for anaphora resolution. Here, the number of nega- tive …...
Annotation Time Stamps — Temporal Metadata from the Linguistic Annotation Process
AbstractWe describe the re-annotation of selected types of named entities (persons, organizations, locations) from the Muc7 corpus. The focus of this annotation initiative is on recording the time needed for …...
Active Learning for Coreference Resolution
We present an active learning method for coreference resolution that is novel in three re- spects. (i) It uses bootstrapped neighborhood pooling, which ensures a class-balanced pool even though gold …...
PATTY: A Taxonomy of Relational Patterns with Semantic Types
This paper presents PATTY: a large resource for textual patterns that denote binary relations between entities. The patterns are semanti- cally typed and organized into a subsumption taxonomy. The PATTY …...
On Synthetic Data for Back Translation
AbstractBack translation (BT) is one of the most significant technologies in NMT research fields. Existing attempts on BT share a common characteristic: they employ either beam search or random sampling …...