Báo cáo khoa học: "Spectral Learning for Non-Deterministic Dependency Parsing" ppt
Báo cáo khoa học: "Selective Sharing for Multilingual Dependency Parsing" pptx
... features.
When performing unsupervised learning for the
target language, we need to marginalize over possi-
ble derivations. Specifically, for the M step, we need
probabilities of the form P (a modifies ... for learning the
syntactic structure of a language. Standard ap-
proaches for extending these techniques to resource-
lean languages either use parallel corpora or rely on
1
The...
Báo cáo khoa học: "Spectral Learning for Non-Deterministic Dependency Parsing" ppt
... paper we study spectral learning
methods for non-deterministic split head-
automata grammars, a powerful hidden-
state formalism for dependency parsing.
We present a learning algorithm that, ... 409–419,
Avignon, France, April 23 - 27 2012.
c
2012 Association for Computational Linguistics
Spectral Learning for Non-Deterministic Dependency Parsing
Franco M. Luque
Univers...
Báo cáo khoa học: "Discriminative Learning for Joint Template Filling" pptx
... the Association for Computational Linguistics, pages 845–853,
Jeju, Republic of Korea, 8-14 July 2012.
c
2012 Association for Computational Linguistics
Discriminative Learning for Joint Template ... for each tar-
get relation, an integrated model to weight the dif-
ferent extraction options, including for example the
likely lengths for events, or the fact that start times
shoul...
Tài liệu Báo cáo khoa học: "Online Learning of Approximate Dependency Parsing Algorithms" potx
... argued for a dependency formal-
ism called Discontinuous Grammar and annotated
a large set of Danish sentences using this formal-
ism to create the Danish Dependency Treebank
(Kromann, 2003). The formalism ... The formulation
works by defining the score of a dependency tree
to be the sum of edge scores,
s(x, y) =
(i,j)∈y
s(i, j)
where x = x
1
· · · x
n
is an input sentence and y
a d...
Báo cáo khoa học: "Optimizing Grammars for Minimum Dependency Length" pptx
... word
order for a set of dependency trees so as
to minimize total dependency length. We
present an algorithm for computing the op-
timal layout of a single tree as well as a
numerical method for optimizing ... provide more informa-
tion for the optimization procedure to work with.
4.3 Learning Curve
How many sentences are necessary to learn a good
set of dependency weights? Tab...
Tài liệu Báo cáo khoa học: "Guided Learning for Bidirectional Sequence Classification" ppt
... our learning algorithm is the strategy
used to select samples for training.
In general, this novel learning framework lies be-
tween supervised learning and reinforcement learn-
ing. Guided learning ... classification are dynamically incorporated in the
learning phase.
Guided learning is not as hard as reinforcement
learning. At each local step in learning, we always
know the u...
Tài liệu Báo cáo khoa học: "Machine Learning for Coreference Resolution: From Local Classification to Global Ranking" ppt
... systems
adopting the standard machine learning approach,
outperforming them by as much as 4–7% on the
three data sets for one of the performance metrics.
2 Related Work
As mentioned before, our approach differs ... and Cardie (2002b) for details.
Learning algorithms. We consider three learning
algorithms, namely, the C4.5 decision tree induction
system (Quinlan, 1993), the RIPPER ru...
Báo cáo khoa học: "Accurate Learning for Chinese Function Tags from Minimal Features" pdf
... applying it to
our specific task.
3.1 Learning Model
The framework from which HM-SVM are derived
is a maximum margin formulation for joint fea-
ture functions in kernel learning setting. Given n
labeled ... satisfactory for practical use.
The limitation is even more pertinent for the lan-
guages that do not have sophisticated parsing re-
sources, or languages that have inherent lingu...
Báo cáo khoa học: "Transductive learning for statistical machine translation" potx
... Linguistics, pages 25–32,
Prague, Czech Republic, June 2007.
c
2007 Association for Computational Linguistics
Transductive learning for statistical machine translation
Nicola Ueffing
National Research Council ... Algorithm 1 we run it for a fixed number
of iterations and instead focus on finding useful def-
initions for Estimate, Score and Select that can be
experimentally shown to im...
Báo cáo khoa học: "Reinforcement Learning for Mapping Instructions to Actions" pdf
... contrast, our emphasis
is on learning language by proactively interacting
with an external environment.
Reinforcement Learning for Language Pro-
cessing Reinforcement learning has been previ-
ously ... divided into 70 for
training, 18 for development, and 40 for test. In
the puzzle game domain, we use 50 tutorials,
divided into 40 for training and 10 for test.
9
Statistics...