5 Search Results for "Potukuchi, Aditya"

Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2020.30
On the List Recoverability of Randomly Punctured Codes

Authors: Ben Lund and Aditya Potukuchi

Published in: LIPIcs, Volume 176, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)

Abstract
We show that a random puncturing of a code with good distance is list recoverable beyond the Johnson bound. In particular, this implies that there are Reed-Solomon codes that are list recoverable beyond the Johnson bound. It was previously known that there are Reed-Solomon codes that do not have this property. As an immediate corollary to our main theorem, we obtain better degree bounds on unbalanced expanders that come from Reed-Solomon codes.
Cite as

Ben Lund and Aditya Potukuchi. On the List Recoverability of Randomly Punctured Codes. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 176, pp. 30:1-30:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{lund_et_al:LIPIcs.APPROX/RANDOM.2020.30,
  author =	{Lund, Ben and Potukuchi, Aditya},
  title =	{{On the List Recoverability of Randomly Punctured Codes}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)},
  pages =	{30:1--30:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-164-1},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{176},
  editor =	{Byrka, Jaros{\l}aw and Meka, Raghu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2020.30},
  URN =		{urn:nbn:de:0030-drops-126330},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2020.30},
  annote =	{Keywords: List recovery, randomly punctured codes, Reed-Solomon codes}
}
Document
DOI: 10.4230/LIPIcs.CCC.2020.31
Connecting Perebor Conjectures: Towards a Search to Decision Reduction for Minimizing Formulas

Authors: Rahul Ilango

Published in: LIPIcs, Volume 169, 35th Computational Complexity Conference (CCC 2020)

Abstract
A longstanding open question is whether there is an equivalence between the computational task of determining the minimum size of any circuit computing a given function and the task of producing a minimum-sized circuit for a given function. While it is widely conjectured that both tasks require "perebor," or brute-force search, researchers have not yet ruled out the possibility that the search problem requires exponential time but the decision problem has a linear time algorithm. In this paper, we make progress in connecting the search and decision complexity of minimizing formulas. Let MFSP denote the problem that takes as input the truth table of a Boolean function f and an integer size parameter s and decides whether there is a formula for f of size at most s. Let Search- denote the corresponding search problem where one has to output some optimal formula for computing f. Our main result is that given an oracle to MFSP, one can solve Search-MFSP in time polynomial in the length N of the truth table of f and the number t of "near-optimal" formulas for f, in particular O(N⁶t²)-time. While the quantity t is not well understood, we use this result (and some extensions) to prove that given an oracle to MFSP: - there is a deterministic 2^O(N/(log log N))-time oracle algorithm for solving Search-MFSP on all but a o(1)-fraction of instances, and - there is a randomized O(2^.67N)-time oracle algorithm for solving Search-MFSP on all instances. Intriguingly, the main idea behind our algorithms is in some sense a "reverse application" of the gate elimination technique.
Cite as

Rahul Ilango. Connecting Perebor Conjectures: Towards a Search to Decision Reduction for Minimizing Formulas. In 35th Computational Complexity Conference (CCC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 169, pp. 31:1-31:35, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{ilango:LIPIcs.CCC.2020.31,
  author =	{Ilango, Rahul},
  title =	{{Connecting Perebor Conjectures: Towards a Search to Decision Reduction for Minimizing Formulas}},
  booktitle =	{35th Computational Complexity Conference (CCC 2020)},
  pages =	{31:1--31:35},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-156-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{169},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2020.31},
  URN =		{urn:nbn:de:0030-drops-125834},
  doi =		{10.4230/LIPIcs.CCC.2020.31},
  annote =	{Keywords: minimum circuit size problem, minimum formula size problem, gate elimination, search to decision reduction, self-reducibility}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2020.93
A Spectral Bound on Hypergraph Discrepancy

Authors: Aditya Potukuchi

Published in: LIPIcs, Volume 168, 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)

Abstract
Let ℋ be a t-regular hypergraph on n vertices and m edges. Let M be the m × n incidence matrix of ℋ and let us denote λ = max_{v ∈ 𝟏^⟂} 1/‖v‖ ‖Mv‖. We show that the discrepancy of ℋ is O(√t + λ). As a corollary, this gives us that for every t, the discrepancy of a random t-regular hypergraph with n vertices and m ≥ n edges is almost surely O(√t) as n grows. The proof also gives a polynomial time algorithm that takes a hypergraph as input and outputs a coloring with the above guarantee.
Cite as

Aditya Potukuchi. A Spectral Bound on Hypergraph Discrepancy. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 93:1-93:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{potukuchi:LIPIcs.ICALP.2020.93,
  author =	{Potukuchi, Aditya},
  title =	{{A Spectral Bound on Hypergraph Discrepancy}},
  booktitle =	{47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)},
  pages =	{93:1--93:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-138-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{168},
  editor =	{Czumaj, Artur and Dawar, Anuj and Merelli, Emanuela},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2020.93},
  URN =		{urn:nbn:de:0030-drops-125002},
  doi =		{10.4230/LIPIcs.ICALP.2020.93},
  annote =	{Keywords: Hypergraph discrepancy, Spectral methods, Beck-Fiala conjecture}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2020.34
Approaching MCSP from Above and Below: Hardness for a Conditional Variant and AC^0[p]

Authors: Rahul Ilango

Published in: LIPIcs, Volume 151, 11th Innovations in Theoretical Computer Science Conference (ITCS 2020)

Abstract
The Minimum Circuit Size Problem (MCSP) asks whether a given Boolean function has a circuit of at most a given size. MCSP has been studied for over a half-century and has deep connections throughout theoretical computer science including to cryptography, computational learning theory, and proof complexity. For example, we know (informally) that if MCSP is easy to compute, then most cryptography can be broken. Despite this cryptographic hardness connection and extensive research, we still know relatively little about the hardness of MCSP unconditionally. Indeed, until very recently it was unknown whether MCSP can be computed in AC^0[2] (Golovnev et al., ICALP 2019). Our main contribution in this paper is to formulate a new "oracle" variant of circuit complexity and prove that this problem is NP-complete under randomized reductions. In more detail, we define the Minimum Oracle Circuit Size Problem (MOCSP) that takes as input the truth table of a Boolean function f, a size threshold s, and the truth table of an oracle Boolean function O, and determines whether there is a circuit with O-oracle gates and at most s wires that computes f. We prove that MOCSP is NP-complete under randomized polynomial-time reductions. We also extend the recent AC^0[p] lower bound against MCSP by Golovnev et al. to a lower bound against the circuit minimization problem for depth-d formulas, (AC^0_d)-MCSP. We view this result as primarily a technical contribution. In particular, our proof takes a radically different approach from prior MCSP-related hardness results.
Cite as

Rahul Ilango. Approaching MCSP from Above and Below: Hardness for a Conditional Variant and AC^0[p]. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 34:1-34:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{ilango:LIPIcs.ITCS.2020.34,
  author =	{Ilango, Rahul},
  title =	{{Approaching MCSP from Above and Below: Hardness for a Conditional Variant and AC^0\lbrackp\rbrack}},
  booktitle =	{11th Innovations in Theoretical Computer Science Conference (ITCS 2020)},
  pages =	{34:1--34:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-134-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{151},
  editor =	{Vidick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2020.34},
  URN =		{urn:nbn:de:0030-drops-117191},
  doi =		{10.4230/LIPIcs.ITCS.2020.34},
  annote =	{Keywords: Minimum Circuit Size Problem, reductions, NP-completeness, circuit lower bounds}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2019.25
On the AC^0[oplus] Complexity of Andreev’s Problem

Authors: Aditya Potukuchi

Published in: LIPIcs, Volume 150, 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)

Abstract
Andreev’s Problem is the following: Given an integer d and a subset of S subset F_q x F_q, is there a polynomial y = p(x) of degree at most d such that for every a in F_q, (a,p(a)) in S? We show an AC^0[oplus] lower bound for this problem. This problem appears to be similar to the list recovery problem for degree-d Reed-Solomon codes over F_q which states the following: Given subsets A_1,...,A_q of F_q, output all (if any) the Reed-Solomon codewords contained in A_1 x *s x A_q. In particular, we study this problem when the lists A_1, ..., A_q are randomly chosen, and are of a certain size. This may be of independent interest.
Cite as

Aditya Potukuchi. On the AC^0[oplus] Complexity of Andreev’s Problem. In 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 150, pp. 25:1-25:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

Copy BibTex To Clipboard

@InProceedings{potukuchi:LIPIcs.FSTTCS.2019.25,
  author =	{Potukuchi, Aditya},
  title =	{{On the AC^0\lbrackoplus\rbrack Complexity of Andreev’s Problem}},
  booktitle =	{39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)},
  pages =	{25:1--25:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-131-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{150},
  editor =	{Chattopadhyay, Arkadev and Gastin, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2019.25},
  URN =		{urn:nbn:de:0030-drops-115879},
  doi =		{10.4230/LIPIcs.FSTTCS.2019.25},
  annote =	{Keywords: List Recovery, Sharp Threshold, Fourier Analysis}
}
  • Refine by Author
  • 3 Potukuchi, Aditya
  • 2 Ilango, Rahul
  • 1 Lund, Ben

  • Refine by Classification
  • 3 Theory of computation → Circuit complexity
  • 2 Theory of computation → Problems, reductions and completeness
  • 1 Mathematics of computing → Discrete mathematics
  • 1 Theory of computation → Error-correcting codes

  • Refine by Keyword
  • 1 Beck-Fiala conjecture
  • 1 Fourier Analysis
  • 1 Hypergraph discrepancy
  • 1 List Recovery
  • 1 List recovery
  • Show More...

  • Refine by Type
  • 5 document

  • Refine by Publication Year
  • 4 2020
  • 1 2019

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact