Does 'sparse' mean different in sparse feature & sparse representation? In Google developers site, the meaning of the word sparse seems to contradict between the following two definitions:

*

*sparse feature:


Feature vector whose values are predominately zero or empty...



*sparse representation:


A representation of a tensor that only stores nonzero elements...


Can someone please help me make better sense out of this?

These concepts reinforce one another once you understand the visual purpose of the latter.  A sparse object is a vector, matrix, etc., that contains a lot of zeroes in it.  Consequently, a more useful representation for showing that thing is the representative form that omits the zeroes, which allows us to concentrate on the relatively small number of non-zero values.  The "sparse feature" and "sparse representation" shown here is an example of this.
I get why you say that these terms appear to be contradictory --- the name "sparse representation" for the latter is really the opposite of what it actually is.  The so-called "sparse representation" is actually more like a "sparse-part-omitted representation" of the original thing.  Presumably the originators of these concepts felt that literal description was a bit too much of a mouthful, and they probably figured that the names given would make sense in the context of understanding why it is good to represent sparse objects in this reduced way.
