We approached the problem as learning how to order documents by estimated relevance with respect to a user query. Our support vector machines based classifier learns from the rele...
Dmitri Roussinov, Weiguo Fan, Fernando A. Das Neve...
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Online advertising is a rapidly growing, multi-billion dollar industry. It has become a significant element of the Web browsing experience. Ad platforms used for ad selection use ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...