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ICML
1997
IEEE
16 years 7 months ago
Hierarchical Explanation-Based Reinforcement Learning
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
Prasad Tadepalli, Thomas G. Dietterich
ICML
1995
IEEE
16 years 7 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
WWW
2008
ACM
16 years 7 months ago
Algorithm for stochastic multiple-choice knapsack problem and application to keywords bidding
We model budget-constrained keyword bidding in sponsored search auctions as a stochastic multiple-choice knapsack problem (S-MCKP) and design an algorithm to solve S-MCKP and the ...
Yunhong Zhou, Victor Naroditskiy
WWW
2008
ACM
16 years 7 months ago
R-U-in?: doing what you like, with people whom you like
This paper presents R-U-In? ? a social networking application that leverages Web 2.0 and IMS-based Converged Networks technologies to create a rich next-generation service. R-U-In...
Nilanjan Banerjee, Dipanjan Chakraborty, Koustuv D...
WWW
2005
ACM
16 years 7 months ago
Adaptive filtering of advertisements on web pages
We present a browser extension to dynamically learn to filter unwanted images (such as advertisements or flashy graphics) based on minimal user feedback. To do so, we apply the we...
Babak Esfandiari, Richard Nock