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» Learning the Structure of Linear Latent Variable Models
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CEC
2009
IEEE
15 years 8 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
15 years 8 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
13 years 4 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»
16 years 2 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
15 years 3 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