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» Approximation Methods for Supervised Learning
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ICML
2006
IEEE
14 years 8 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil
ICTAI
2006
IEEE
14 years 1 months ago
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents
In order for an autonomous agent to behave robustly in a variety of environments, it must have the ability to learn approximations to many different functions. The function approx...
Daniel Stronger, Peter Stone
COLING
2010
13 years 2 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang
IJCAI
2007
13 years 9 months ago
Graph-Based Semi-Supervised Learning as a Generative Model
This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
Jingrui He, Jaime G. Carbonell, Yan Liu 0002
AI
2005
Springer
14 years 1 months ago
A Supervised Learning Approach to Acronym Identification
This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular ...
David Nadeau, Peter D. Turney