Caleb Robelle

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5ranked-venue papers
0as first author
4since 2021 · last 2023
—ORCID · none

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Theory of computation · 4 · 4 since 2021Systems, architecture and hardware · 1
YearPublicationVenuePosition
2023 Cryptographic hardness under projections for time-bounded Kolmogorov complexity
Eric Allender, John Gouwar, Shuichi Hirahara, Caleb Robelle
Theor. Comput. Sci.4
2022 Partially Optimal Edge Fault-Tolerant Spanners
abstract
Recent work has established that, for every positive integer k, every n-node graph has a (2k–1)-spanner with O(f1–1/k n1+1/k) edges that is resilient to f edge or vertex faults. For vertex faults, this bound is tight. However, the case of edge faults is not as well understood: the best known lower bound for general k is . Our main result is to nearly close this gap with an improved upper bound, thus separating the cases of edge and vertex faults. For odd k, our new upper bound is , which is tight up to hidden poly(k) factors. For even k, our new upper bound is Ok(f1/2 n1 + 1/k + fn), which leaves a gap of poly(k)f1/(2k). Our proof is an analysis of the fault-tolerant greedy algorithm, which requires exponential time, but we also show that there is a polynomial-time algorithm which creates edge fault tolerant spanners that are larger only by factors of k.
Gregory Bodwin, Michael Dinitz, Caleb Robelle
SODA3
2021 Cryptographic Hardness Under Projections for Time-Bounded Kolmogorov Complexity
abstract
A version of time-bounded Kolmogorov complexity, denoted KT, has received attention in the past several years, due to its close connection to circuit complexity and to the Minimum Circuit Size Problem MCSP. Essentially all results about the complexity of MCSP hold also for MKTP (the problem of computing the KT complexity of a string). Both MKTP and MCSP are hard for SZK (Statistical Zero Knowledge) under BPP-Turing reductions; neither is known to be NP-complete. Recently, some hardness results for MKTP were proved that are not (yet) known to hold for MCSP. In particular, MKTP is hard for DET (a subclass of P) under nonuniform ≤^{NC^0}_m reductions. In this paper, we improve this, to show that the complement of MKTP is hard for the (apparently larger) class NISZK_L under not only ≤^{NC^0}_m reductions but even under projections. Also, the complement of MKTP is hard for NISZK under ≤^{P/poly}_m reductions. Here, NISZK is the class of problems with non-interactive zero-knowledge proofs, and NISZK_L is the non-interactive version of the class SZK_L that was studied by Dvir et al. As an application, we provide several improved worst-case to average-case reductions to problems in NP, and we obtain a new lower bound on MKTP (which is currently not known to hold for MCSP).
Eric Allender, John Gouwar, Shuichi Hirahara, Caleb Robelle
ISAAC4
2021 Optimal Vertex Fault-Tolerant Spanners in Polynomial Time
abstract
Recent work has pinned down the existentially optimal size bounds for vertex fault-tolerant spanners: for any positive integer k, every n-node graph has a (2k – 1)-spanner on O(f1–1/kn1+1/k) edges resilient to f vertex faults, and there are examples of input graphs on which this bound cannot be improved. However, these proofs work by analyzing the output spanner of a certain exponential-time greedy algorithm. In this work, we give the first algorithm that produces vertex fault tolerant spanners of optimal size and which runs in polynomial time. Specifically, we give a randomized algorithm which takes Õ (f1–1/kn2+1/k + mf2) time. We also derandomize our algorithm to give a deterministic algorithm with similar bounds. This reflects an exponential improvement in runtime over [Bodwin-Patel PODC '19], the only previously known algorithm for constructing optimal vertex fault-tolerant spanners.
Gregory Bodwin, Michael Dinitz, Caleb Robelle
SODA3
2020 Efficient and Simple Algorithms for Fault-Tolerant Spanners
abstract
It was recently shown that a version of the greedy algorithm gives a construction of fault-tolerant spanners that is size-optimal, at least for vertex faults. However, the algorithm to construct this spanner is not polynomial-time, and the best-known polynomial time algorithm is significantly suboptimal. Designing a polynomial-time algorithm to construct (near-)optimal fault-tolerant spanners was given as an explicit open problem in the two most recent papers on fault-tolerant spanners ([Bodwin, Dinitz, Parter, Vassilevka Williams SODA '18] and [Bodwin, Patel PODC '19]). We give a surprisingly simple algorithm which runs in polynomial time and constructs fault-tolerant spanners that are extremely close to optimal (off by only a linear factor in the stretch) by modifying the greedy algorithm to run in polynomial time. To complement this result, we also give simple distributed constructions in both the LOCAL and CONGEST models.
Michael Dinitz, Caleb Robelle
PODC2