The fifth man, an officer, has different representation.
For instance, an object can have different representations for each LOD which enables analysis and visualization of the same object with several degrees of resolution (Groger and Plumer 2012).
Inputs are given by (mathbf {x}_{mathcal {T}}(n)) and (mathbf {x}_{mathcal {S}}(n)) for teacher and student, respectively, and may have different representations but are time synchronous.
Note that in any of the representations mentioned in the cases, different people have different representations because they are selective in attention, represent stimuli in the context of interests and pre-knowledge, and add and delete information to fit a view which is comfortable to them.
Some of the fundamental parts of REST when applied to HTTP and URIs are: Resources are targets of references and are identified by resource identifiers in the form of URIs Resources can have different representations (formats), e.g. HTML, XML, JSON (JavaScript Object Notation), plain text, serialized Java objects.
Those datasets are generated from a variety of sources having different representation forms and formats.
These results suggest that empathy toward non conspecifics has different neural representation among individuals with different feeding habits, perhaps reflecting different motivational factors and beliefs.
Teacher and student networks may have different input representations, sizes, and architectures.
We have extended this soft target training framework in a new and useful way by pairing teacher and student networks that have different input representations.
This work adds to the growing empirical evidence that training with soft targets from an accurate teacher is an effective method of training NNs and extends the soft target training concept in a new and useful way by pairing teacher and student networks which have different input representations.
