Sciweavers

ACL
2004
13 years 10 months ago
Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins, Mark...
AIA
2007
13 years 11 months ago
Classification of biomedical high-resolution micro-CT images for direct volume rendering
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
Maite López-Sánchez, Jesús Ce...
ACL
2008
13 years 11 months ago
A Generic Sentence Trimmer with CRFs
The paper presents a novel sentence trimmer in Japanese, which combines a non-statistical yet generic tree generation model and Conditional Random Fields (CRFs), to address improv...
Tadashi Nomoto
ACL
2008
13 years 11 months ago
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
Gideon S. Mann, Andrew McCallum
CIKM
2008
Springer
13 years 11 months ago
Closing the loop in webpage understanding
The two most important tasks in information extraction from the Web are webpage structure understanding and natural language sentences processing. However, little work has been don...
Chunyu Yang, Yong Cao, Zaiqing Nie, Jie Zhou, Ji-R...
CIKM
2008
Springer
13 years 11 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
AAAI
2008
13 years 11 months ago
Learning to Analyze Binary Computer Code
We present a novel application of structured classification: identifying function entry points (FEPs, the starting byte of each function) in program binaries. Such identification ...
Nathan E. Rosenblum, Xiaojin Zhu, Barton P. Miller...
AAAI
2008
13 years 11 months ago
Constrained Classification on Structured Data
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...
Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner...
AAAI
2008
13 years 11 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
AAAI
2008
13 years 11 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso