We have various types of data features with different temporal scale. For example, some of them describe the state per second while others may describe the state per day or per month from another aspect. The former features are dense on the time scale and latter features are sparse. Simply concatenate them into one feature vector seems not proper. Is there any typical method in machine learning can handle with problem ?