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EPIA
2003
Springer
15 years 11 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas
NIPS
2007
15 years 7 months ago
Stability Bounds for Non-i.i.d. Processes
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
Mehryar Mohri, Afshin Rostamizadeh
ML
1998
ACM
115views Machine Learning» more  ML 1998»
15 years 6 months ago
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL
This paper is a case study of a machine aided knowledge discovery process within the general area of drug design. More speci cally, the paper describes a sequence of experiments in...
Paul W. Finn, Stephen Muggleton, David Page, Ashwi...
NIPS
1998
15 years 7 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 9 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich