We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
We present methods employed in COORDINATE, a prototype service that supports collaboration and communication by learning predictive models that provide forecasts of users' pr...
Joe Tullio, James Begole, Eric Horvitz, Elizabeth ...
Abstract. Local air quality forecasting can be made on the basis of meteorological and air pollution time series. Such data contain redundant information. Partial mutual informatio...
Crop forecast is an activity practiced by experts in agriculture, based on large data volumes. These data cover climatological information of the most diverse types, concerning a g...
Demand forecast plays a critical role to determine capital investment for capacity planning. Given the involved uncertainties and long lead-time for capacity expansion, semiconduc...