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AAAI
1994
15 years 7 months ago
Recovering Software Specifications with Inductive Logic Programming
We consider using machine learning techniques to help understand a large software system. In particular, we describe how learning techniques can be used to reconstruct abstract Da...
William W. Cohen
AIED
2009
Springer
16 years 1 months ago
I learn from you, you learn from me: How to make iList learn from students
We developed a new model for iList, our system that helps students learn linked list. The model is automatically extracted from past student data, and allows iList to track student...
Davide Fossati, Barbara Di Eugenio, Stellan Ohlsso...
AAAI
2011
14 years 6 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou
ICONIP
1998
15 years 7 months ago
Inducing Relational Concepts with Neural Networks via the LINUS System
This paper presents a method to induce relational concepts with neural networks using the inductive logic programming system LINUS. Some first-order inductive learning tasks taken...
Rodrigo Basilio, Gerson Zaverucha, Artur S. d'Avil...
FPL
2009
Springer
156views Hardware» more  FPL 2009»
15 years 11 months ago
A highly scalable Restricted Boltzmann Machine FPGA implementation
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
Sang Kyun Kim, Lawrence C. McAfee, Peter L. McMaho...