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» Learning on the Test Data: Leveraging Unseen Features
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KDD
2007
ACM
167views Data Mining» more  KDD 2007»
14 years 9 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
NIPS
2003
13 years 10 months ago
Unsupervised Context Sensitive Language Acquisition from a Large Corpus
We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
IAAI
2003
13 years 10 months ago
Searching for Hidden Messages: Automatic Detection of Steganography
Steganography is the field of hiding messages in apparently innocuous media (e.g. images), and steganalysis is the field of detecting these covert messages. Almost all steganalysi...
George Berg, Ian Davidson, Ming-Yuan Duan, Goutam ...
UAI
2003
13 years 10 months ago
Robust Independence Testing for Constraint-Based Learning of Causal Structure
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Denver Dash, Marek J. Druzdzel
TSP
2010
13 years 3 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...