ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Predicting the "Value at Risk" of a portfolio of stocks is of great significance in quantitative finance. We introduce a new class models, "dynamical products of ex...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. In this work we introduce a mathematical theory for Artificial Prediction ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...