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CIMCA
2005
IEEE
15 years 7 months ago
Opposition-Based Learning: A New Scheme for Machine Intelligence
Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions...
Hamid R. Tizhoosh
NSDI
2008
15 years 4 months ago
Exploiting Machine Learning to Subvert Your Spam Filter
Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical m...
Blaine Nelson, Marco Barreno, Fuching Jack Chi, An...
COLT
2008
Springer
15 years 4 months ago
Learning Random Monotone DNF Under the Uniform Distribution
We show that randomly generated monotone c log(n)-DNF formula can be learned exactly in probabilistic polynomial time. Our notion of randomly generated is with respect to a unifor...
Linda Sellie
SEKE
2007
Springer
15 years 8 months ago
An Approach to Software Testing of Machine Learning Applications
Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Chris Murphy, Gail E. Kaiser, Marta Arias
CORR
2002
Springer
96views Education» more  CORR 2002»
15 years 2 months ago
Thumbs up? Sentiment Classification using Machine Learning Techniques
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, w...
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan