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CIKM
2010
Springer
13 years 3 months ago
A unified optimization framework for robust pseudo-relevance feedback algorithms
We present a flexible new optimization framework for finding effective, reliable pseudo-relevance feedback models that unifies existing complementary approaches in a principled wa...
Joshua V. Dillon, Kevyn Collins-Thompson
TREC
2008
13 years 6 months ago
Extending Relevance Model for Relevance Feedback
Relevance feedback is the retrieval task where the system is given not only an information need, but also some relevance judgement information, usually from users' feedback f...
Le Zhao, Chenmin Liang, Jamie Callan
AIRS
2009
Springer
13 years 11 months ago
A Latent Dirichlet Framework for Relevance Modeling
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
Viet Ha-Thuc, Padmini Srinivasan
ISCAS
2011
IEEE
231views Hardware» more  ISCAS 2011»
12 years 8 months ago
A unified optimization framework for simultaneous gate sizing and placement under density constraints
—A unified optimization framework is presented for simultaneous gate sizing and placement. These processes are unified using Lagrangian multipliers, which synchronize the efforts...
Jason Cong, John Lee, Guojie Luo
CEC
2010
IEEE
13 years 4 months ago
Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling
Abstract— We present a unifying framework for continuous optimization and sampling. This framework is based on Gaussian Adaptation (GaA), a search heuristic developed in the late...
Christian L. Müller, Ivo F. Sbalzarini