Robust Optimization over Multiple Domains

Understand

In this work, we study the problem of learning a single model for multiple domains.

• Unlike the conventional machine learning scenario where each domain can have the corresponding model, multiple domains (i.e., applications/users) may share the same machine learning model due to maintenance loads in cloud computing services.
• For example, a digit-recognition model should be applicable to hand-written digits, house numbers, car plates, etc.
• Therefore, an ideal model for cloud computing has to perform well at each applicable domain.