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ICDE
2012
IEEE
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11 years 7 months ago
Scalable and Numerically Stable Descriptive Statistics in SystemML
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
Yuanyuan Tian, Shirish Tatikonda, Berthold Reinwal...
ECOOP
2011
Springer
12 years 4 months ago
Frequency Estimation of Virtual Call Targets for Object-Oriented Programs
Abstract. The information of execution frequencies of virtual call targets is valuable for program analyses and optimizations of object-oriented programs. However, to obtain this i...
Cheng Zhang, Hao Xu, Sai Zhang, Jianjun Zhao, Yuti...
AAAI
2011
12 years 5 months ago
Effective End-User Interaction with Machine Learning
End-user interactive machine learning is a promising tool for enhancing human productivity and capabilities with large unstructured data sets. Recent work has shown that we can cr...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
AIED
2011
Springer
12 years 8 months ago
Workflow-Based Assessment of Student Online Activities with Topic and Dialogue Role Classification
The Pedagogical Assessment Workflow System (PAWS) is a new workflow-based pedagogical assessment framework that enables the efficient and robust integration of diverse datasets for...
Jun Ma, Jeon-Hyung Kang, Erin Shaw, Jihie Kim
ICMLA
2003
13 years 6 months ago
Fast Class-Attribute Interdependence Maximization (CAIM) Discretization Algorithm
– Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an a...
Lukasz A. Kurgan, Krzysztof J. Cios
NIPS
2001
13 years 6 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
NIPS
2004
13 years 6 months ago
Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)
Machine learning is often used to automatically solve human tasks. In this paper, we look for tasks where machine learning algorithms are not as good as humans with the hope of ga...
Kumar Chellapilla, Patrice Y. Simard
HIS
2004
13 years 6 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai
EACL
2006
ACL Anthology
13 years 6 months ago
Automatic Acronym Recognition
This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym rec...
Dana Dannélls
DAGSTUHL
2004
13 years 6 months ago
Learning with Local Models
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
Stefan Rüping