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» Domain Adaptation for Statistical Classifiers
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JMLR
2012
11 years 10 months ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...
EMNLP
2008
13 years 9 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
CICLING
2001
Springer
13 years 12 months ago
Chi-Square Classifier for Document Categorization
The problem of document categorization is considered. The set of domains and the keywords specific for these domains is supposed to be selected beforehand as initial data. We apply...
Mikhail Alexandrov, Alexander F. Gelbukh, George L...
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 7 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
CORR
1999
Springer
67views Education» more  CORR 1999»
13 years 7 months ago
Robust Combining of Disparate Classifiers through Order Statistics
: Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this arti...
Kagan Tumer, Joydeep Ghosh