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IJCNLP
2005
Springer
14 years 1 months ago
Regularisation Techniques for Conditional Random Fields: Parameterised Versus Parameter-Free
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets. Conventional approaches to regu...
Andrew Smith, Miles Osborne
JMLR
2010
145views more  JMLR 2010»
13 years 2 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
AI
1998
Springer
13 years 7 months ago
Utility-Based On-Line Exploration for Repeated Navigation in an Embedded Graph
In this paper, we address the tradeo between exploration and exploitation for agents which need to learn more about the structure of their environment in order to perform more e e...
Shlomo Argamon-Engelson, Sarit Kraus, Sigalit Sina
RECOMB
2004
Springer
14 years 7 months ago
A random graph approach to NMR sequential assignment
Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...
Chris Bailey-Kellogg, Sheetal Chainraj, Gopal Pand...
ICPP
2008
IEEE
14 years 2 months ago
On the Design of Fast Pseudo-Random Number Generators for the Cell Broadband Engine and an Application to Risk Analysis
Numerical simulations in computational physics, biology, and finance, often require the use of high quality and efficient parallel random number generators. We design and optimi...
David A. Bader, Aparna Chandramowlishwaran, Virat ...