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» Learning with Weighted Transducers
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NIPS
1993
13 years 10 months ago
Optimal Stochastic Search and Adaptive Momentum
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
Todd K. Leen, Genevieve B. Orr
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 9 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
CORR
2010
Springer
100views Education» more  CORR 2010»
13 years 9 months ago
Products of Weighted Logic Programs
Abstract. Weighted logic programming, a generalization of bottom-up logic programming, is a successful framework for specifying dynamic programming algorithms. In this setting, pro...
Shay B. Cohen, Robert J. Simmons, Noah A. Smith
SIGIR
2011
ACM
12 years 12 months ago
Parameterized concept weighting in verbose queries
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
Michael Bendersky, Donald Metzler, W. Bruce Croft
TSP
2010
13 years 3 months ago
Multichannel fast QR-decomposition algorithms: weight extraction method and its applications
Abstract--Multichannel fast QR decomposition RLS (MCFQRD-RLS) algorithms are well known for their good numerical properties and low computational complexity. The main limitation is...
Mobien Shoaib, Stefan Werner, José Antonio ...