3 ms·
Is there any abstraction of Deep Learning on discrete domains? Using discrete calculus from Concrete Mathematics perhaps? Or better a mixed discrete/continuous
by bitL 8y ago
Is there any abstraction of Deep Learning on discrete domains? Using discrete calculus from Concrete Mathematics perhaps? Or better a mixed discrete/continuous one? I guess optimization there would be killer...
- pests 8y agoThere are many different ways to represent discrete domains in deep learning. One example is entity embeddings such as word2vec which turns a finite list of entities (words in word2vec) into a number of continuous variables.
- bitL 8y agoI know. Though if you want to represent complex DAGs or do some inner combinatorics, it doesn't generalize that well. DeepWalk and its variations are only for toy-sized graphs.