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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > PROBABILISTIC DEGREE:
Reports tagged with Probabilistic degree:
TR19-138 | 6th October 2019
Srikanth Srinivasan, Utkarsh Tripathi, S Venkitesh

On the Probabilistic Degrees of Symmetric Boolean functions

The probabilistic degree of a Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ is defined to be the smallest $d$ such that there is a random polynomial $\mathbf{P}$ of degree at most $d$ that agrees with $f$ at each point with high probability. Introduced by Razborov (1987), upper and lower bounds on probabilistic degrees ... more >>>


TR20-046 | 13th April 2020
Srikanth Srinivasan

A Robust Version of Heged\H{u}s's Lemma, with Applications

Heged\H{u}s's lemma is the following combinatorial statement regarding polynomials over finite fields. Over a field $\mathbb{F}$ of characteristic $p > 0$ and for $q$ a power of $p$, the lemma says that any multilinear polynomial $P\in \mathbb{F}[x_1,\ldots,x_n]$ of degree less than $q$ that vanishes at all points in $\{0,1\}^n$ of ... more >>>


TR21-098 | 7th July 2021
Srikanth Srinivasan, S Venkitesh

On the Probabilistic Degree of an $n$-variate Boolean Function

Nisan and Szegedy (CC 1994) showed that any Boolean function $f:\{0,1\}^n\to\{0,1\}$ that depends on all its input variables, when represented as a real-valued multivariate polynomial $P(x_1,\ldots,x_n)$, has degree at least $\log n - O(\log \log n)$. This was improved to a tight $(\log n - O(1))$ bound by Chiarelli, Hatami ... more >>>




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