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TASLP
2010
109views more  TASLP 2010»
13 years 2 months ago
Multipitch Estimation of Piano Sounds Using a New Probabilistic Spectral Smoothness Principle
Abstract--A new method for the estimation of multiple concurrent pitches in piano recordings is presented. It addresses the issue of overlapping overtones by modeling the spectral ...
Valentin Emiya, Roland Badeau, Bertrand David
ICML
2009
IEEE
14 years 8 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
ICRA
2009
IEEE
218views Robotics» more  ICRA 2009»
13 years 5 months ago
Automatically and efficiently inferring the hierarchical structure of visual maps
In Simultaneous Localisation and Mapping (SLAM), it is well known that probabilistic filtering approaches which aim to estimate the robot and map state sequentially suffer from poo...
Margarita Chli, Andrew J. Davison
AAAI
2011
12 years 7 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
TIP
2008
133views more  TIP 2008»
13 years 7 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky