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Electronic Colloquium on Computational Complexity

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All reports by Author Graham Cormode:

TR14-086 | 11th July 2014
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler, Suresh Venkatasubramanian

Verifiable Stream Computation and Arthur–Merlin Communication

In the setting of streaming interactive proofs (SIPs), a client (verifier) needs to compute a given function on a massive stream of data, arriving online, but is unable to store even a small fraction of the data. It outsources the processing to a third party service (prover), but is unwilling ... more >>>

TR13-180 | 17th December 2013
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler, Suresh Venkatasubramanian

On Interactivity in Arthur-Merlin Communication and Stream Computation

Revisions: 1

We introduce {\em online interactive proofs} (OIP), which are a hierarchy of communication complexity models that involve both randomness and nondeterminism (thus, they belong to the Arthur--Merlin family), but are {\em online} in the sense that the basic communication flows from Alice to Bob alone. The complexity classes defined by ... more >>>

TR12-022 | 14th March 2012
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler

Annotations in Data Streams

Revisions: 1

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 >>>

TR11-105 | 22nd July 2011
Graham Cormode, Michael Mitzenmacher, Justin Thaler

Streaming Graph Computations with a Helpful Advisor

Revisions: 1

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 >>>

TR11-062 | 18th April 2011
Amit Chakrabarti, Graham Cormode, Andrew McGregor

Robust Lower Bounds for Communication and Stream Computation

We study the communication complexity of evaluating functions when the input data is randomly allocated (according to some known distribution) amongst two or more players, possibly with information overlap. This naturally extends previously studied variable partition models such as the best-case and worst-case partition models. We aim to understand whether ... more >>>

TR10-159 | 28th October 2010
Graham Cormode, Justin Thaler, Ke Yi

Verifying Computations with Streaming Interactive Proofs

Applications based on outsourcing computation require guarantees to the data owner that the desired computation has been performed correctly by the service provider. Methods based on proof systems can give the data owner the necessary assurance, but previous work does not give a sufficiently scalable and practical solution, requiring a ... more >>>

TR10-076 | 18th April 2010
Amit Chakrabarti, Graham Cormode, Ranganath Kondapally, Andrew McGregor

Information Cost Tradeoffs for Augmented Index and Streaming Language Recognition

Revisions: 1

This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of AUGMENTED-INDEX. In contrast to analogous results for INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the significant technical challenge that ... more >>>

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