Báo cáo khoa học: "Semi-Supervised Active Learning for Sequence Labeling" pptx
Báo cáo khoa học: "Semi-Supervised Active Learning for Sequence Labeling" pptx
... as confidence
estimators.
3 Active Learning for Sequence Labeling
AL is a selective sampling technique where the
learning protocol is in control of the data to be
used for training. The intention ... utility functions for
sequence labeling. We have chosen this straightforward one
for simplicity and because it has proven to be very effective
(Settles and Craven, 2008).
For t...
Báo cáo khoa học: "Heterogeneous Transfer Learning for Image Clustering via the Social Web" docx
... hetero-
geneous transfer learning relates to other types of
learning, Figure 1 presents an intuitive illustration
of four learning strategies, including traditional
machine learning, transfer learning across ... in Transfer Learning
In the past, several other works made use of trans-
fer learning for cross-feature-space learning. Wu
and Oard (2008) proposed to handle the cross-...
Báo cáo khoa học: "Structural Correspondence Learning for Parse Disambiguation" pot
... Greece, 2 April 2009.
c
2009 Association for Computational Linguistics
Structural Correspondence Learning for Parse Disambiguation
Barbara Plank
Alfa-informatica
University of Groningen, The Netherlands
b.plank@rug.nl
Abstract
The ... of
Structural Correspondence Learning
(SCL) (Blitzer et al., 2006) for domain
adaptation of a stochastic attribute-value
grammar (SAVG). So far, SCL...
Báo cáo khoa học: "Hierarchical Sequential Learning for Extracting Opinions and their Attributes" ppt
... construc-
tion. For instance, one can add λ
δ
g
I
(δ, x, i)
and λ
′
δ,
ˆ
δ
g
′
I
(δ,
ˆ
δ, x, i) to Equation (1) for δ ∈
{0, 1, , 9}, in order to allow more individualized
learning for each label.
Notice ... Hierarchical Sequential Learning
We define the problem of joint extraction of opin-
ion expressions and their attributes as a sequence
tagging task as follows. Given a sequence...
Báo cáo khoa học: "Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm" doc
... co-training is how to
select informative samples. Active learning ap-
proaches, such as Muslea et al. (2000), can gener-
ally select more informative samples, for example,
samples for which two classifiers ... data.
Finally we compared our co-training perfor-
mance with supervised learning. For supervised
learning, all labeled utterances except for the test
set are used for tra...
Báo cáo khoa học: "Weakly Supervised Learning for Hedge Classification in Scientific Literature" pot
... such ideas can be adapted for this task is
one of many avenues for future research.
10.6 Error Analysis
Some errors are due to the variety of hedge forms.
For example, the learning models were unsuccess-
ful ... avenues
for future research.
1 Introduction
The automatic processing of scientific papers using
NLP and machine learning (ML) techniques is an
increasingly important aspect...
Báo cáo khoa học: "An Active Learning Approach to Finding Related Terms" docx
... improves perfor-
mance. For example, L(MWD,+) outscores
U(MWD,+) by 19%. Using active learning also
significantly improves performance: L(MWD,+)
outscores L(MWD,-) by 13%. This shows that
active learning ... time and effort might be
saved by using active learning to find good sug-
gestions. Also, as Vyas et al. (2009) show, non-
expert users often produce poor-quality seed sets.
3...
Báo cáo khoa học: "Unsupervised Multilingual Learning for Morphological Segmentation" potx
... pages 737–745,
Columbus, Ohio, USA, June 2008.
c
2008 Association for Computational Linguistics
Unsupervised Multilingual Learning for Morphological Segmentation
Benjamin Snyder and Regina Barzilay
Computer ... of information for automatic lin-
guistic analysis as well. In this paper we investi-
gate two questions: (i) Can we exploit cross-lingual
correspondences to improve unsupervi...
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