University of Birmingham > Talks@bham > Theoretical computer science seminar > Model Counting meets F0 Estimation

Model Counting meets F0 Estimation

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Constraint satisfaction problems (CSP) and data stream models are two powerful abstractions to capture a wide variety of problems arising in different domains of computer science. Developments in the two communities have mostly occurred independently and with little interaction between them. In this work, we seek to investigate whether bridging the seeming communication gap between the two communities may pave the way to richer fundamental insights.

In this talk, I will describe how our investigations lead us to observe striking similarity in the core techniques employed in the algorithmic frameworks that have evolved separately for model counting and F0 computation. We design a simple recipe for translation of algorithms developed for F0 estimation to that of model counting, resulting in new algorithms for model counting. We then observe that algorithms in the context of distributed streaming can be transformed to distributed algorithms for model counting. We next turn our attention to viewing streaming from the lens of counting and show that framing F0 estimation as a special case of #DNF counting allows us to obtain a general recipe for a rich class of streaming problems, which had been subjected to case-specific analysis in prior works.

(Joint work with A. Pavan, N. V. Vinodchandran, A. Bhattacharyya. The paper appeared at PODS 2021 , invited to ACM TODS as “Best of PODS 2021 ” and received 2022 ACM SIGMOD Research Highlight Award).

This talk will be chaired by Rajesh Chitnis.

This talk is part of the Theoretical computer science seminar series.

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