We present a flexible new optimization framework for finding effective, reliable pseudo-relevance feedback models that unifies existing complementary approaches in a principled wa...
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...
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 ...
—A unified optimization framework is presented for simultaneous gate sizing and placement. These processes are unified using Lagrangian multipliers, which synchronize the efforts...
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...