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ICML
2010
IEEE
13 years 11 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
ICML
2006
IEEE
14 years 11 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
CVPR
2012
IEEE
12 years 18 days ago
3D landmark model discovery from a registered set of organic shapes
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...
Clement Creusot, Nick Pears, Jim Austin
ICML
2006
IEEE
14 years 11 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto
ICML
2007
IEEE
14 years 11 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum