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7 years 4 months ago
Road Scene Understanding from a Single Image
Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes ...
Jose M. Alvarez, Theo Gevers, Yann LeCun, Antonio ...
ML
2010
ACM
135views Machine Learning» more  ML 2010»
8 years 8 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
TNN
2011
200views more  TNN 2011»
8 years 8 months ago
Domain Adaptation via Transfer Component Analysis
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...
EMNLP
2010
8 years 11 months ago
We're Not in Kansas Anymore: Detecting Domain Changes in Streams
Domain adaptation, the problem of adapting a natural language processing system trained in one domain to perform well in a different domain, has received significant attention. Th...
Mark Dredze, Tim Oates, Christine D. Piatko
PAMI
2010
122views more  PAMI 2010»
8 years 12 months ago
Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
Lorenzo Bruzzone, Mattia Marconcini
EMNLP
2008
9 years 3 months ago
Online Methods for Multi-Domain Learning and Adaptation
NLP tasks are often domain specific, yet systems can learn behaviors across multiple domains. We develop a new multi-domain online learning framework based on parameter combinatio...
Mark Dredze, Koby Crammer
EMNLP
2007
9 years 3 months ago
Frustratingly Hard Domain Adaptation for Dependency Parsing
We describe some challenges of adaptation in the 2007 CoNLL Shared Task on Domain Adaptation. Our error analysis for this task suggests that a primary source of error is differenc...
Mark Dredze, John Blitzer, Partha Pratim Talukdar,...
COLING
2008
9 years 3 months ago
On Robustness and Domain Adaptation using SVD for Word Sense Disambiguation
In this paper we explore robustness and domain adaptation issues for Word Sense Disambiguation (WSD) using Singular Value Decomposition (SVD) and unlabeled data. We focus on the s...
Eneko Agirre, Oier Lopez de Lacalle
ACL
2007
9 years 3 months ago
Instance Weighting for Domain Adaptation in NLP
Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation prob...
Jing Jiang, ChengXiang Zhai
ACL
2007
9 years 3 months ago
Domain Adaptation with Active Learning for Word Sense Disambiguation
When a word sense disambiguation (WSD) system is trained on one domain but applied to a different domain, a drop in accuracy is frequently observed. This highlights the importance...
Yee Seng Chan, Hwee Tou Ng
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