Observational medical data present unique opportunities for analysis of outcomes and treatment decision making. However, because these datasets do not contain the strict pairing randomized control trials, matching techniques are to draw comparisons among patients. A key limitation such is verification that variables used model making also relevant in identifying risk major adverse events. This ...

This paper proposes the use of a regularized mixture linear experts (MoLE) for predictive modeling in multimode-multiphase industrial processes. For this purpose, different MoLE were evaluated, namely, through elastic net (EN), Lasso, and ridge regression (RR) penalties. Their performances compared when trained with numbers samples, comparison to other nonlinear models. The models evaluated on ...

This paper introduces a neural network capable of dynamically adapting its architecture to model a task that can change with time. This network has its roots in the mixture of experts framework. Modules or Experts are grown or pruned depending on the (changing) complexity of the modeling problem. On-line updates of all parameters make it suitable for time varying environments. Simulation result...

We discuss a class of nonlinear models based on mixtures-of-experts of regressions of exponential family time series models, where the covariates include functions of lags of the dependent variable as well as external covariates. The discussion covers results on model identifiability, stochastic stability, parameter estimation via maximum likelihood estimation, and model selection via standard ...

Machine classi cation of acoustic waveforms as speech events is often di cult due to context-dependencies. A vowel recognition task with multiple speakers is studied in this paper via the use of a class of modular and hierarchical systems referred to as mixtures-of-experts and hierarchical mixtures-of-experts models. The statistical model underlying the systems is a mixture model in which both ...

Hand gestures have great potential to act as a computer interface in the entertainment environment. However, there are two major problems when implementing the hand gesture-based interface for multiple users, the complexity problem and the personalization problem. In order to solve these problems and implement multi-user data glove interface successfully, we propose an adaptive mixture-of-exper...

Imbalanced training sample means that one class is represented by a large number of examples while the other is represented by only a few. This problem may produce an important deterioration of the classifier performance, in particular with patterns belonging to the less represented classes. The majority of the studies in this area are oriented, mainly, to resolve problems with two classes. How...

We present GMMbuilder, a tool that allows domain scientists to build Gaussian Mixture Models (GMM) that adhere to domain specific constraints like spatial coherence. Domain experts use this tool to generate different models, extract stable object communities across these models, and use these communities to interactively design a final clustering model that explains the data but also considers ...