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» Hedging predictions in machine learning
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ICML
2009
IEEE
16 years 5 months ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino
ICML
1998
IEEE
15 years 8 months ago
The Problem with Noise and Small Disjuncts
Many systems that learn from examples express the learned concept as a disjunction. Those disjuncts that cover only a few examples are referred to as small disjuncts. The problem ...
Gary M. Weiss, Haym Hirsh
ALT
2008
Springer
16 years 1 months ago
Learning with Continuous Experts Using Drifting Games
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Indraneel Mukherjee, Robert E. Schapire
ICML
2010
IEEE
15 years 5 months ago
Large Graph Construction for Scalable Semi-Supervised Learning
In this paper, we address the scalability issue plaguing graph-based semi-supervised learning via a small number of anchor points which adequately cover the entire point cloud. Cr...
Wei Liu, Junfeng He, Shih-Fu Chang
ICML
2007
IEEE
16 years 5 months ago
Restricted Boltzmann machines for collaborative filtering
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called R...
Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hin...