The nature of statistical learning theory
The nature of statistical learning theory
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Machine Learning
The Role of Occam‘s Razor in Knowledge Discovery
Data Mining and Knowledge Discovery
Preventing "Overfitting" of Cross-Validation Data
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A Unifeid Bias-Variance Decomposition and its Applications
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Bayesian Averaging of Classifiers and the Overfitting Problem
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Mining complex models from arbitrarily large databases in constant time
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
The lack of a priori distinctions between learning algorithms
Neural Computation
Controlled experiments on the web: survey and practical guide
Data Mining and Knowledge Discovery
Learning Deep Architectures for AI
Foundations and Trends® in Machine Learning
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
EvoBIO'13 Proceedings of the 11th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Data science for software engineering
Proceedings of the 2013 International Conference on Software Engineering
Predicting user activity level in social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Expert Systems with Applications: An International Journal
Bias-variance tradeoffs in program analysis
Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages
Feature engineering for semantic place prediction
Pervasive and Mobile Computing
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Tapping into the "folk knowledge" needed to advance machine learning applications.