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» Learning the Structure of Linear Latent Variable Models
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CEC
2009
IEEE
14 years 2 months ago
Evolving hypernetwork models of binary time series for forecasting price movements on stock markets
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...
IDA
2009
Springer
14 years 2 months ago
Blind Spectral-GMM Estimation for Underdetermined Instantaneous Audio Source Separation
Abstract. The underdetermined blind audio source separation problem is often addressed in the time-frequency domain by assuming that each time-frequency point is an independently d...
Simon Arberet, Alexey Ozerov, Rémi Gribonva...
JMLR
2012
11 years 10 months ago
Sample Complexity of Composite Likelihood
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
Joseph K. Bradley, Carlos Guestrin
KDD
2007
ACM
211views Data Mining» more  KDD 2007»
14 years 8 months ago
Enhanced max margin learning on multimodal data mining in a multimedia database
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...
NIPS
2008
13 years 9 months ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton