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CORR
2000
Springer
99views Education» more  CORR 2000»
13 years 10 months ago
Adaptive simulated annealing (ASA): Lessons learned
Adaptive simulated annealing (ASA) is a global optimization algorithm based on an associated proof that the parameter space can be sampled much more efficiently than by using othe...
Lester Ingber
CORR
2010
Springer
47views Education» more  CORR 2010»
13 years 9 months ago
Applications of Lindeberg Principle in Communications and Statistical Learning
We use a generalization of the Lindeberg principle developed by Sourav Chatterjee to prove universality properties for various problems in communications, statistical learning and...
Satish Babu Korada, Andrea Montanari
EMNLP
2010
13 years 8 months ago
Learning the Relative Usefulness of Questions in Community QA
We present a machine learning approach for the task of ranking previously answered questions in a question repository with respect to their relevance to a new, unanswered referenc...
Razvan C. Bunescu, Yunfeng Huang
CVPR
2009
IEEE
15 years 5 months ago
Active Learning for Large Multi-class Problems
Scarcity and infeasibility of human supervision for large scale multi-class classification problems necessitates active learning. Unfortunately, existing active learning methods ...
Prateek Jain (University of Texas at Austin), Ashi...
GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
14 years 5 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiï...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...