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» Learning Relational Concepts with Decision Trees
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ICMLA
2010
13 years 5 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
INFORMATICASI
1998
122views more  INFORMATICASI 1998»
13 years 7 months ago
Experimental Evaluation of Three Partition Selection Criteria for Decision Table Decomposition
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
Blaz Zupan, Marko Bohanec
AAAI
1998
13 years 9 months ago
Iterated Phantom Induction: A Little Knowledge Can Go a Long Way
Weadvance a knowledge-based learning method that augments conventional generalization to permit concept acquisition in failure domains. These are domains in whichlearning must pro...
Mark Brodie, Gerald DeJong
IJHCI
2010
144views more  IJHCI 2010»
13 years 6 months ago
Naturalistic Decision Making for Power System Operators
Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To ...
Frank L. Greitzer, Robin Podmore, Marck Robinson, ...
STOC
1994
ACM
128views Algorithms» more  STOC 1994»
13 years 11 months ago
Weakly learning DNF and characterizing statistical query learning using Fourier analysis
We present new results on the well-studied problem of learning DNF expressions. We prove that an algorithm due to Kushilevitz and Mansour [13] can be used to weakly learn DNF form...
Avrim Blum, Merrick L. Furst, Jeffrey C. Jackson, ...