Graham Cormode, Michael Mitzenmacher, Justin Thaler

Motivated by the trend to outsource work to commercial cloud computing services, we consider a variation of the streaming paradigm where a streaming algorithm can be assisted by a powerful helper that can provide annotations to the data stream. We extend previous work on such annotation models by considering a ... more >>>

Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler

The central goal of data stream algorithms is to process massive streams of data using sublinear storage space. Motivated by work in the database community on outsourcing database and data stream processing, we ask whether the space usage of such algorithms can be further reduced by enlisting a more powerful ... more >>>

Toniann Pitassi, Morgan Shirley, Adi Shraibman

It is well-known that randomized communication protocols are more powerful than deterministic protocols. In particular the Equality function requires $\Omega(n)$ deterministic communication complexity but has efficient randomized protocols. Previous work of Chattopadhyay, Lovett and Vinyals shows that randomized communication is strictly stronger than what can be solved by deterministic protocols ... more >>>