When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
: The generic problem of estimation and inference given a sequence of i.i.d. samples has been extensively studied in the statistics, property testing, and learning communities. A n...
To benefit from a location-based service, a person must reveal her location to the service. However, knowing the person’s location might allow the service to re-identify the pe...
Existing ML-like languages guarantee type-safety, ensuring memty and protecting the invariants of abstract types, but only within single executions of single programs. Distributed...
John Billings, Peter Sewell, Mark R. Shinwell, Rok...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...