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SIGIR
2005
ACM
15 years 9 months ago
Personalizing search via automated analysis of interests and activities
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
Jaime Teevan, Susan T. Dumais, Eric Horvitz
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
15 years 8 months ago
The maximum hypervolume set yields near-optimal approximation
In order to allow a comparison of (otherwise incomparable) sets, many evolutionary multiobjective optimizers use indicator functions to guide the search and to evaluate the perfor...
Karl Bringmann, Tobias Friedrich
127
Voted
TCC
2007
Springer
100views Cryptology» more  TCC 2007»
15 years 9 months ago
Private Approximation of Clustering and Vertex Cover
Private approximation of search problems deals with finding approximate solutions to search problems while disclosing as little information as possible. The focus of this work is ...
Amos Beimel, Renen Hallak, Kobbi Nissim
159
Voted
ATAL
2005
Springer
15 years 9 months ago
Improving reinforcement learning function approximators via neuroevolution
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...
Shimon Whiteson
MICAI
2005
Springer
15 years 8 months ago
Proximity Searching in High Dimensional Spaces with a Proximity Preserving Order
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Edgar Chávez, Karina Figueroa, Gonzalo Nava...