... 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...
... Active Learning for Statistical Natural Language Parsing
Min Tang
Spoken Language Systems Group
MIT Laboratory for Computer Science
Cambridge, Massachusetts ... to
achieve a satisfactory performance using active learning.
Active learning has been studied in the context of many
natural language processing (NLP) applications such as
information extraction(Thompson ... cluste...
... 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...
... 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 ... June 2005.
c
2005 Association for Computational Linguistics
Machine Learning for Coreference Resolution:
From Local Classification to Global Ranking
Vincent Ng
Human Lan...
... tags directly
from lexical information, which is eas-
ily scalable for languages that lack suf-
ficient parsing resources or have inher-
ent linguistic challenges for parsing. We
investigated ... 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 linguistic
challen...
... sentence-aligned with each other
and all translate into the same target language. One
language pair creates data for another language pair
and can be naturally used in a (Blum and Mitchell,
1998)-style co-training ... Our hypothesis is that adding infor-
mation from source language text can also provide
improvements. Unlike adding target language text,
this hypothesis is a natural...
... 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, ... of Human Language Technology Conference
and Conference on Empirical Methods in Natural
Language Processing, pages 523–530, Vancouver,
British Columbia, Canada, October. Association for...
... 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 ... ac-
tions that emit natural language utterances. The
reinforcement learning state space encodes infor-
mation about the goals of the user and what they
say at each time step....