All reports by Author Suprovat Ghoshal:

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TR19-079
| 28th May 2019
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Arnab Bhattacharyya, Philips George John, Suprovat Ghoshal, Raghu Meka#### Average Bias and Polynomial Sources

Revisions: 2

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TR18-057
| 26th March 2018
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Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi#### Parameterized Intractability of Even Set and Shortest Vector Problem from Gap-ETH

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TR17-115
| 5th July 2017
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Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket#### Hardness of learning noisy halfspaces using polynomial thresholds

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TR15-193
| 26th November 2015
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Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket#### On the hardness of learning sparse parities

Arnab Bhattacharyya, Philips George John, Suprovat Ghoshal, Raghu Meka

We identify a new notion of pseudorandomness for randomness sources, which we call the average bias. Given a distribution $Z$ over $\{0,1\}^n$, its average bias is: $b_{\text{av}}(Z) =2^{-n} \sum_{c \in \{0,1\}^n} |\mathbb{E}_{z \sim Z}(-1)^{\langle c, z\rangle}|$. A source with average bias at most $2^{-k}$ has min-entropy at least $k$, and ... more >>>

Arnab Bhattacharyya, Suprovat Ghoshal, Karthik C. S., Pasin Manurangsi

The $k$-Even Set problem is a parameterized variant of the Minimum Distance Problem of linear codes over $\mathbb F_2$, which can be stated as follows: given a generator matrix $\mathbf A$ and an integer $k$, determine whether the code generated by $\mathbf A$ has distance at most $k$. Here, $k$ ... more >>>

Arnab Bhattacharyya, Suprovat Ghoshal, Rishi Saket

We prove the hardness of weakly learning halfspaces in the presence of adversarial noise using polynomial threshold functions (PTFs). In particular, we prove that for any constants $d \in \mathbb{Z}^+$ and $\epsilon > 0$, it is NP-hard to decide: given a set of $\{-1,1\}$-labeled points in $\mathbb{R}^n$ whether (YES Case) ... more >>>

Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket

This work investigates the hardness of computing sparse solutions to systems of linear equations over $\mathbb{F}_2$. Consider the $k$-EvenSet problem: given a homogeneous system of linear equations over $\mathbb{F}_2$ on $n$ variables, decide if there exists a nonzero solution of Hamming weight at most $k$ (i.e. a $k$-sparse solution). While ... more >>>