In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, ...
Abstract: In real-world applications, deep neural networks may encounter constantly changing environments, where the test data originates from continually shifting unlabeled target domains. This ...
Abstract: There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this paper we ...