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Electronic Colloquium on Computational Complexity

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All reports by Author Swagato Sanyal:

TR18-014 | 10th January 2018
Swagato Sanyal

A Composition Theorem via Conflict Complexity

Let $\R(\cdot)$ stand for the bounded-error randomized query complexity. We show that for any relation $f \subseteq \{0,1\}^n \times \mathcal{S}$ and partial Boolean function $g \subseteq \{0,1\}^n \times \{0,1\}$, $\R_{1/3}(f \circ g^n) = \Omega(\R_{4/9}(f) \cdot \sqrt{\R_{1/3}(g)})$. Independently of us, Gavinsky, Lee and Santha \cite{newcomp} proved this result. By an example ... more >>>

TR17-152 | 9th October 2017
Swagato Sanyal

One-way Communication and Non-adaptive Decision Tree

Comments: 1

Let $f$ be a Boolean function on $n$-bits, and $\mathsf{IP}$ the inner-product function on $2b$ bits. Let $f^{\mathsf{IP}}:=f \circ \mathsf{IP}^n$ be the two party function obtained by composing $f$ with $\mathsf{IP}$. In this work we bound the one-way communication complexity of $f^{\IP}$ in terms of the non-adaptive query complexity of ... more >>>

TR17-123 | 2nd August 2017
Dmitry Gavinsky, Rahul Jain, Hartmut Klauck, Srijita Kundu, Troy Lee, Miklos Santha, Swagato Sanyal, Jevgenijs Vihrovs

Quadratically Tight Relations for Randomized Query Complexity

Let $f:\{0,1\}^n \rightarrow \{0,1\}$ be a Boolean function. The certificate complexity $C(f)$ is a complexity measure that is quadratically tight for the zero-error randomized query complexity $R_0(f)$: $C(f) \leq R_0(f) \leq C(f)^2$. In this paper we study a new complexity measure that we call expectational certificate complexity $EC(f)$, which is ... more >>>

TR17-107 | 1st June 2017
Anurag Anshu, Dmitry Gavinsky, Rahul Jain, Srijita Kundu, Troy Lee, Priyanka Mukhopadhyay, Miklos Santha, Swagato Sanyal

A Composition Theorem for Randomized Query complexity

Revisions: 1

Let the randomized query complexity of a relation for error probability $\epsilon$ be denoted by $\R_\epsilon(\cdot)$. We prove that for any relation $f \subseteq \{0,1\}^n \times \mathcal{R}$ and Boolean function $g:\{0,1\}^m \rightarrow \{0,1\}$, $\R_{1/3}(f\circ g^n) = \Omega(\R_{4/9}(f)\cdot\R_{1/2-1/n^4}(g))$, where $f \circ g^n$ is the relation obtained by composing $f$ and $g$. ... more >>>

TR16-103 | 6th July 2016
Jaikumar Radhakrishnan, Swagato Sanyal

The zero-error randomized query complexity of the pointer function.

The pointer function of G{\"{o}}{\"{o}}s, Pitassi and Watson
\cite{DBLP:journals/eccc/GoosP015a} and its variants have recently
been used to prove separation results among various measures of
complexity such as deterministic, randomized and quantum query
complexities, exact and approximate polynomial degrees, etc. In
particular, the widest possible (quadratic) separations between
deterministic and zero-error ... more >>>

TR15-107 | 21st June 2015
Sagnik Mukhopadhyay, Swagato Sanyal

Towards Better Separation between Deterministic and Randomized Query Complexity

We show that there exists a Boolean function $F$ which observes the following separations among deterministic query complexity $(D(F))$, randomized zero error query complexity $(R_0(F))$
and randomized one-sided error query complexity $(R_1(F))$: $R_1(F) = \widetilde{O}(\sqrt{D(F)})$ and $R_0(F)=\widetilde{O}(D(F))^{3/4}$. This refutes the conjecture made by
Saks and Wigderson that for any Boolean ... more >>>

TR14-088 | 13th July 2014
Swagato Sanyal

Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity

Revisions: 1 , Comments: 1

We prove that the Fourier dimension of any Boolean function with
Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof
method yields an improved bound of $\widetilde{O}(\sqrt{s})$
assuming a conjecture of Tsang~\etal~\cite{tsang}, that for every
Boolean function of sparsity $s$ there is an affine subspace of
more >>>

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