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ICML
2010
IEEE
14 years 18 days ago
Dynamical Products of Experts for Modeling Financial Time Series
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...
Yutian Chen, Max Welling
ICML
2010
IEEE
14 years 18 days ago
Multiagent Inductive Learning: an Argumentation-based Approach
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...
Santiago Ontañón, Enric Plaza
ICML
2010
IEEE
14 years 18 days ago
Learning Deep Boltzmann Machines using Adaptive MCMC
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...
Ruslan Salakhutdinov
ICML
2010
IEEE
14 years 18 days ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
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...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
ICML
2010
IEEE
14 years 18 days ago
Telling cause from effect based on high-dimensional observations
Dominik Janzing, Patrik O. Hoyer, Bernhard Sch&oum...
ICML
2010
IEEE
14 years 18 days ago
The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
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...
Sinead Williamson, Chong Wang, Katherine A. Heller...
ICML
2010
IEEE
14 years 18 days ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
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 ...
Noam Goldberg, Jonathan Eckstein
ICML
2010
IEEE
14 years 18 days ago
Supervised Aggregation of Classifiers using Artificial Prediction Markets
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 ...
Nathan Lay, Adrian Barbu
ICML
2010
IEEE
14 years 18 days ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
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...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...