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ML
2008
ACM
13 years 11 months ago
Discovering significant patterns
Pattern discovery techniques, such as association rule discovery, explore large search spaces of potential patterns to find those that satisfy some user-specified constraints. Due...
Geoffrey I. Webb
ML
2008
ACM
128views Machine Learning» more  ML 2008»
13 years 11 months ago
QG/GA: a stochastic search for Progol
Most search techniques within ILP require the evaluation of a large number of inconsistent clauses. However, acceptable clauses typically need to be consistent, and are only found ...
Stephen Muggleton, Alireza Tamaddoni-Nezhad
ML
2008
ACM
146views Machine Learning» more  ML 2008»
13 years 11 months ago
Improving maximum margin matrix factorization
Abstract. Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful lear...
Markus Weimer, Alexandros Karatzoglou, Alex J. Smo...
ML
2008
ACM
101views Machine Learning» more  ML 2008»
13 years 11 months ago
On reoptimizing multi-class classifiers
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
ML
2008
ACM
13 years 11 months ago
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns
Standard pattern discovery techniques, such as association rules, suffer an extreme risk of finding very large numbers of spurious patterns for many knowledge discovery tasks. The...
Geoffrey I. Webb
ML
2008
ACM
100views Machine Learning» more  ML 2008»
13 years 11 months ago
Compressing probabilistic Prolog programs
Luc De Raedt, Kristian Kersting, Angelika Kimmig, ...
ML
2008
ACM
100views Machine Learning» more  ML 2008»
13 years 11 months ago
Generalized ordering-search for learning directed probabilistic logical models
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendri...
ML
2008
ACM
13 years 11 months ago
Large margin vs. large volume in transductive learning
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
ML
2008
ACM
13 years 11 months ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski
ML
2008
ACM
152views Machine Learning» more  ML 2008»
13 years 11 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...