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133
Voted
CVPR
2009
IEEE
16 years 8 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
101
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
104
Voted
COLT
2007
Springer
15 years 6 months ago
2007
Springer
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
132
Voted
NIPS
1997
15 years 2 months ago
1997
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
123
click to vote
ICML
1996
IEEE
16 years 1 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...