Distributed Stochastic Graph Algorithms
Pith reviewed 2026-05-21 04:02 UTC · model grok-4.3
The pith
Stochastic distributed algorithms achieve faster approximations for matching and covering by using only realized random edges.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
We establish that distributed stochastic algorithms can be drastically faster than their non-stochastic counterparts and overcome known lower bounds, by showing fast distributed approximation algorithms for maximum matching, minimum vertex cover, and minimum dominating set.
What carries the argument
The stochastic distributed model with local knowledge of realized edges in the random subgraph G*, which restricts communication to those edges and enables reduced round complexity.
If this is right
- Maximum matching admits fast distributed approximations that beat non-stochastic lower bounds.
- Minimum vertex cover can be approximated in significantly fewer rounds using the stochastic model.
- Minimum dominating set similarly receives fast distributed approximations.
- The approach demonstrates that randomness in edge realizations can be exploited directly for efficiency gains.
Where Pith is reading between the lines
- The same local-realization technique could extend to other graph problems such as coloring or shortest paths.
- Real-world networks with probabilistic link formation might adopt this model for more efficient distributed protocols.
- Limited communication over non-realized edges could be added while retaining some of the observed speedups.
Load-bearing premise
Each vertex receives exact knowledge of its incident realized edges and communicates exclusively over those realized edges.
What would settle it
A proof establishing that the same approximation problems still require as many rounds in this model as in the non-stochastic case, even with local knowledge of realized edges.
Figures
read the original abstract
We study stochastic graph optimization problems in a novel distributed setting. As in the standard centralized setting, a random subgraph $G^*$ of a known base graph $G$ is realized by including each edge $e$ independently with a known probability $p_e$, and we must solve an optimization problem on $G^*$ despite uncertainty about its edges. In the standard setting, to cope with this uncertainty, the algorithm can query any edge of $G$ to learn if the edge exists in $G^*$, and its complexity is the number of queried edges. The distributed setting incorporates uncertainty in a natural manner, by having each vertex know only about its own edges in $G^*$ (and only communicate over them), and the complexity is measured by the number of synchronous communication rounds. We establish that distributed stochastic algorithms can be drastically faster than their non-stochastic counterparts and overcome known lower bounds, by showing fast distributed approximation algorithms for maximum matching, minimum vertex cover, and minimum dominating set.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript introduces a distributed model for stochastic graph optimization on a random subgraph G* realized from a known base graph G, where each edge is included independently with probability p_e. Vertices receive exact local knowledge of their incident realized edges in G* and communicate exclusively over those edges, with complexity measured in synchronous rounds. The central claim is that this model enables drastically faster distributed approximation algorithms for maximum matching, minimum vertex cover, and minimum dominating set compared to non-stochastic counterparts, overcoming known lower bounds.
Significance. If the algorithms and their analyses hold, the work is significant for demonstrating how a natural incorporation of stochastic uncertainty—via local knowledge of realized edges and restricted communication—can bypass standard lower bounds in distributed graph algorithms. The concrete results on three classic problems provide falsifiable predictions and a clear model definition that distinguishes this setting from centralized stochastic optimization or standard distributed models. This opens avenues for efficient distributed computation under uncertainty.
minor comments (3)
- The abstract would be strengthened by explicitly stating the approximation ratios achieved and the round complexities for each of the three problems.
- A comparison table or section contrasting the new stochastic distributed model with the LOCAL/CONGEST models and with centralized stochastic query models would improve clarity for readers.
- Notation for the base graph G, realized subgraph G*, and edge probabilities p_e is introduced clearly but could be reinforced with a formal definition early in the model section.
Simulated Author's Rebuttal
We thank the referee for the positive summary, recognition of the model's novelty in incorporating stochastic uncertainty via local realized-edge knowledge, and recommendation for minor revision. The assessment accurately reflects the central claim that the distributed stochastic setting enables approximation algorithms for matching, vertex cover, and dominating set that bypass non-stochastic lower bounds.
Circularity Check
No significant circularity detected
full rationale
The paper presents new distributed algorithms for stochastic graph problems (maximum matching, minimum vertex cover, minimum dominating set) in a model where each vertex knows its realized incident edges in G* and communicates only over them. The central claims consist of algorithmic constructions and round-complexity bounds that are derived from the algorithm descriptions and their analysis; these do not reduce to fitted parameters, self-definitions, or load-bearing self-citations. The modeling assumptions are stated explicitly and the speed-up results are scoped to that model, making the derivation self-contained against external benchmarks.
Axiom & Free-Parameter Ledger
Lean theorems connected to this paper
-
IndisputableMonolith/Foundation/RealityFromDistinction.leanreality_from_one_distinction unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
We study stochastic graph optimization problems in a novel distributed setting... fast distributed approximation algorithms for maximum matching, minimum vertex cover, and minimum dominating set.
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
Works this paper leans on
-
[1]
Censor-Hillel, Keren and Dudeja, Aditi and Giakkoupis, George , title =. 2026 , month = may, url =
work page 2026
-
[2]
An Optimal Algorithm for Stochastic Vertex Cover , journal =
Jan van den Brand and Inge Li G. An Optimal Algorithm for Stochastic Vertex Cover , journal =. 2026 , xurl =. doi:10.48550/arXiv.2603.27795 , xeprinttype =
-
[3]
Distributed Computation with Local Advice , booktitle =
Alkida Balliu and Sebastian Brandt and Fabian Kuhn and Krzysztof Nowicki and Dennis Olivetti and Eva Rotenberg and Jukka Suomela , xeditor =. Distributed Computation with Local Advice , booktitle =. 2025 , xurl =. doi:10.4230/LIPICS.DISC.2025.12 , timestamp =
-
[4]
Pierre Fraigniaud and Amos Korman and Emmanuelle Lebhar , title =. Theory Comput. Syst. , volume =. 2010 , xurl =. doi:10.1007/S00224-010-9280-9 , timestamp =
-
[5]
Pierre Fraigniaud and Cyril Gavoille and David Ilcinkas and Andrzej Pelc , title =. Distributed Comput. , volume =. 2009 , xurl =. doi:10.1007/S00446-008-0076-Y , timestamp =
-
[6]
Joan Boyar and Faith Ellen and Kim S. Larsen , title =. CoRR , volume =. 2025 , xurl =. doi:10.48550/ARXIV.2501.05267 , eprinttype =. 2501.05267 , timestamp =
-
[7]
Local Distributed Rounding: Generalized to MIS, Matching, Set Cover, and Beyond , booktitle =
Salwa Faour and Mohsen Ghaffari and Christoph Grunau and Fabian Kuhn and V. Local Distributed Rounding: Generalized to MIS, Matching, Set Cover, and Beyond , booktitle =. 2023 , xurl =. doi:10.1137/1.9781611977554.CH168 , timestamp =
-
[8]
Michal Dory and Mohsen Ghaffari and Saeed Ilchi , title =. Distributed Comput. , volume =. 2024 , xurl =. doi:10.1007/S00446-023-00447-Z , timestamp =
-
[9]
Deterministic Distributed Dominating Set Approximation in the
Janosch Deurer and Fabian Kuhn and Yannic Maus , xeditor =. Deterministic Distributed Dominating Set Approximation in the. 2019. 2019 , xurl =. doi:10.1145/3293611.3331626 , timestamp =
-
[10]
Derandomizing Distributed Algorithms with Small Messages: Spanners and Dominating Set , booktitle =
Mohsen Ghaffari and Fabian Kuhn , xeditor =. Derandomizing Distributed Algorithms with Small Messages: Spanners and Dominating Set , booktitle =. 2018 , xurl =. doi:10.4230/LIPICS.DISC.2018.29 , timestamp =
-
[11]
Fabian Kuhn and Thomas Moscibroda and Roger Wattenhofer , title =. J. 2016 , xurl =. doi:10.1145/2742012 , timestamp =
-
[12]
Constant-time distributed dominating set approximation , booktitle =
Fabian Kuhn and Roger Wattenhofer , xeditor =. Constant-time distributed dominating set approximation , booktitle =. 2003 , xurl =. doi:10.1145/872035.872040 , timestamp =
-
[13]
Improved Deterministic Network Decomposition , booktitle =
Mohsen Ghaffari and Christoph Grunau and V. Improved Deterministic Network Decomposition , booktitle =. 2021 , xurl =. doi:10.1137/1.9781611976465.173 , timestamp =
-
[14]
Adir Morgan and Shay Solomon and Nicole Wein , xeditor =. Algorithms for the Minimum Dominating Set Problem in Bounded Arboricity Graphs: Simpler, Faster, and Combinatorial , booktitle =. 2021 , xurl =. doi:10.4230/LIPICS.DISC.2021.33 , timestamp =
-
[15]
Distributed Spanner Approximation , journal =
Keren Censor. Distributed Spanner Approximation , journal =. 2021 , xurl =. doi:10.1137/20M1312630 , timestamp =
-
[16]
Stochastic Matching on Uniformly Sparse Graphs , booktitle =
Soheil Behnezhad and Mahsa Derakhshan and Alireza Farhadi and MohammadTaghi Hajiaghayi and Nima Reyhani , xeditor =. Stochastic Matching on Uniformly Sparse Graphs , booktitle =. 2019 , xurl =. doi:10.1007/978-3-030-30473-7\_24 , timestamp =
-
[17]
Stochastic Matching via In-n-Out Local Computation Algorithms , booktitle =
Amir Azarmehr and Soheil Behnezhad and Alma Ghafari and Ronitt Rubinfeld , xeditor =. Stochastic Matching via In-n-Out Local Computation Algorithms , booktitle =. 2025 , xurl =. doi:10.1145/3717823.3718279 , timestamp =
-
[18]
Dickerson and Nika Haghtalab and Ariel D
Avrim Blum and John P. Dickerson and Nika Haghtalab and Ariel D. Procaccia and Tuomas Sandholm and Ankit Sharma , xeditor =. Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries , booktitle =. 2015 , xurl =. doi:10.1145/2764468.2764479 , timestamp =
-
[19]
Deterministic Distributed Edge-Coloring via Hypergraph Maximal Matching , booktitle =
Manuela Fischer and Mohsen Ghaffari and Fabian Kuhn , xeditor =. Deterministic Distributed Edge-Coloring via Hypergraph Maximal Matching , booktitle =. 2017 , xurl =. doi:10.1109/FOCS.2017.25 , timestamp =
-
[20]
Local, distributed weighted matching on general and wireless topologies , booktitle =
Tim Nieberg , xeditor =. Local, distributed weighted matching on general and wireless topologies , booktitle =. 2008 , xurl =. doi:10.1145/1400863.1400880 , timestamp =
-
[21]
Joan Boyar and Faith Ellen and Kim S. Larsen , xeditor =. Brief Announcement: Distributed Graph Algorithms with Predictions , booktitle =. 2025 , xurl =. doi:10.1145/3732772.3733530 , timestamp =
-
[22]
Query Complexity of Stochastic Minimum Vertex Cover , booktitle =
Mahsa Derakhshan and Mohammad Saneian and Zhiyang Xun , xeditor =. Query Complexity of Stochastic Minimum Vertex Cover , booktitle =. 2025 , xurl =. doi:10.4230/LIPICS.ITCS.2025.41 , timestamp =
-
[23]
Zvi Lotker and Elan Pavlov and Boaz Patt. Fifteenth. 2003 , xurl =. doi:10.1145/777412.777428 , timestamp =
-
[24]
Korhonen and Ami Paz and Joel Rybicki and Stefan Schmid and Jukka Suomela , xeditor =
Janne H. Korhonen and Ami Paz and Joel Rybicki and Stefan Schmid and Jukka Suomela , xeditor =. Brief Announcement: Sinkless Orientation Is Hard Also in the Supported. 35th International Symposium on Distributed Computing,. 2021 , xurl =. doi:10.4230/LIPICS.DISC.2021.58 , timestamp =
-
[25]
Alkida Balliu and Janne H. Korhonen and Fabian Kuhn and Henrik Lievonen and Dennis Olivetti and Shreyas Pai and Ami Paz and Joel Rybicki and Stefan Schmid and Jan Studen. Sinkless Orientation Made Simple , booktitle =. 2023 , xurl =. doi:10.1137/1.9781611977585.CH17 , timestamp =
-
[26]
Input-Dynamic Distributed Algorithms for Communication Networks , journal =
Klaus. Input-Dynamic Distributed Algorithms for Communication Networks , journal =. 2021 , xurl =. doi:10.1145/3447384 , timestamp =
-
[27]
Local Recurrent Problems in the
Akanksha Agrawal and John Augustine and David Peleg and Srikkanth Ramachandran , xeditor =. Local Recurrent Problems in the. 27th International Conference on Principles of Distributed Systems,. 2023 , xurl =. doi:10.4230/LIPICS.OPODIS.2023.22 , timestamp =
-
[28]
Universally-optimal distributed algorithms for known topologies , booktitle =
Bernhard Haeupler and David Wajc and Goran Zuzic , xeditor =. Universally-optimal distributed algorithms for known topologies , booktitle =. 2021 , xurl =. doi:10.1145/3406325.3451081 , timestamp =
-
[29]
Ioannis Anagnostides and Christoph Lenzen and Bernhard Haeupler and Goran Zuzic and Themis Gouleakis , title =. Distributed Comput. , volume =. 2023 , xurl =. doi:10.1007/S00446-023-00454-0 , timestamp =
-
[30]
Does Preprocessing Help under Congestion? , booktitle =
Klaus. Does Preprocessing Help under Congestion? , booktitle =. 2019 , xurl =. doi:10.1145/3293611.3331581 , timestamp =
-
[31]
On the Power of Preprocessing in Decentralized Network Optimization , booktitle =
Klaus. On the Power of Preprocessing in Decentralized Network Optimization , booktitle =. 2019 , xurl =. doi:10.1109/INFOCOM.2019.8737382 , timestamp =
-
[32]
Tight Lower Bounds in the Supported
Alkida Balliu and Thomas Boudier and Sebastian Brandt and Dennis Olivetti , xeditor =. Tight Lower Bounds in the Supported. 43rd. 2024 , xurl =. doi:10.1145/3662158.3662798 , timestamp =
-
[33]
Korhonen and Joel Rybicki , xeditor =
Janne H. Korhonen and Joel Rybicki , xeditor =. Deterministic Subgraph Detection in Broadcast. 21st International Conference on Principles of Distributed Systems,. 2017 , xurl =. doi:10.4230/LIPICS.OPODIS.2017.4 , timestamp =
-
[34]
Exploiting locality in distributed
Stefan Schmid and Jukka Suomela , xeditor =. Exploiting locality in distributed. Second. 2013 , xurl =. doi:10.1145/2491185.2491198 , timestamp =
-
[35]
Distributed Weighted Matching , booktitle =
Mirjam Wattenhofer and Roger Wattenhofer , xeditor =. Distributed Weighted Matching , booktitle =. 2004 , xurl =. doi:10.1007/978-3-540-30186-8\_24 , timestamp =
-
[36]
Distributed Approximate Matching , journal =
Zvi Lotker and Boaz Patt. Distributed Approximate Matching , journal =. 2009 , xurl =. doi:10.1137/080714403 , timestamp =
-
[37]
Yi. Narrowing the. 2022. 2022 , xurl =. doi:10.1145/3519270.3538423 , timestamp =
-
[38]
Improved Distributed Approximate Matching , journal =
Zvi Lotker and Boaz Patt. Improved Distributed Approximate Matching , journal =. 2015 , xurl =. doi:10.1145/2786753 , timestamp =
-
[39]
(1- )-Approximate Maximum Weighted Matching in poly(1/ , log
Shang. (1- )-Approximate Maximum Weighted Matching in poly(1/ , log. 2023. 2023 , xurl =. doi:10.1145/3583668.3594570 , timestamp =
-
[40]
A framework for boosting matching approximation: parallel, distributed, and dynamic , journal =
Slobodan Mitrovic and Wen. A framework for boosting matching approximation: parallel, distributed, and dynamic , journal =. 2025 , xurl =. doi:10.48550/ARXIV.2503.01147 , eprinttype =
-
[41]
Manuela Fischer , title =. Distributed Comput. , volume =. 2020 , xurl =. doi:10.1007/S00446-018-0344-4 , timestamp =
-
[42]
Manuela Fischer and Slobodan Mitrovic and Jara Uitto , xeditor =. Deterministic (1+. 54th. 2022 , xurl =. doi:10.1145/3519935.3520039 , timestamp =
-
[43]
Naoki Kitamura and Taisuke Izumi , title =. 2022 , xurl =. doi:10.1587/TRANSINF.2021EDP7083 , timestamp =
-
[44]
Distributed Approximate Maximum Matching in the
Mohamad Ahmadi and Fabian Kuhn and Rotem Oshman , xeditor =. Distributed Approximate Maximum Matching in the. 32nd International Symposium on Distributed Computing,. 2018 , xurl =. doi:10.4230/LIPICS.DISC.2018.6 , timestamp =
-
[45]
A Nearly Linear-Time Distributed Algorithm for Exact Maximum Matching , booktitle =
Taisuke Izumi and Naoki Kitamura and Yutaro Yamaguchi , xeditor =. A Nearly Linear-Time Distributed Algorithm for Exact Maximum Matching , booktitle =. 2024 , xurl =. doi:10.1137/1.9781611977912.141 , timestamp =
-
[46]
Yi. The Complexity of Distributed Approximation of Packing and Covering Integer Linear Programs , booktitle =. 2023 , xurl =. doi:10.1145/3583668.3594562 , timestamp =
-
[47]
Improved Deterministic Distributed Matching via Rounding , booktitle =
Manuela Fischer , xeditor =. Improved Deterministic Distributed Matching via Rounding , booktitle =. 2017 , xurl =. doi:10.4230/LIPICS.DISC.2017.17 , timestamp =
-
[48]
Leonid Barenboim and Michael Elkin and Seth Pettie and Johannes Schneider , title =. 53rd. 2012 , xurl =. doi:10.1109/FOCS.2012.60 , timestamp =
-
[49]
Michal Hanckowiak and Michal Karonski and Alessandro Panconesi , title =. 2001 , xurl =. doi:10.1137/S0895480100373121 , timestamp =
-
[50]
Alessandro Panconesi and Romeo Rizzi , title =. Distributed Comput. , volume =. 2001 , xurl =. doi:10.1007/PL00008932 , timestamp =
-
[51]
Valentin Polishchuk and Jukka Suomela , title =. Inf. Process. Lett. , volume =. 2009 , xurl =. doi:10.1016/J.IPL.2009.02.017 , timestamp =
-
[52]
Matti. Fast distributed approximation algorithms for vertex cover and set cover in anonymous networks , booktitle =. 2010 , xurl =. doi:10.1145/1810479.1810533 , timestamp =
-
[53]
A Local 2-Approximation Algorithm for the Vertex Cover Problem , booktitle =
Matti. A Local 2-Approximation Algorithm for the Vertex Cover Problem , booktitle =. 2009 , xurl =. doi:10.1007/978-3-642-04355-0\_21 , timestamp =
-
[54]
Parameterized Distributed Algorithms , booktitle =
Ran Ben. Parameterized Distributed Algorithms , booktitle =. 2019 , xurl =. doi:10.4230/LIPICS.DISC.2019.6 , timestamp =
-
[55]
Optimal distributed covering algorithms , journal =
Ran Ben. Optimal distributed covering algorithms , journal =. 2023 , xurl =. doi:10.1007/S00446-021-00391-W , timestamp =
-
[56]
A Deterministic Distributed 2-Approximation for Weighted Vertex Cover in
Ran Ben. A Deterministic Distributed 2-Approximation for Weighted Vertex Cover in. 25th International Colloquium on Structural Information and Communication Complexity,. 2018 , xurl =. doi:10.1007/978-3-030-01325-7\_21 , timestamp =
-
[57]
Christos Koufogiannakis and Neal E. Young , xeditor =. Distributed and parallel algorithms for weighted vertex cover and other covering problems , booktitle =. 2009 , xurl =. doi:10.1145/1582716.1582746 , timestamp =
-
[58]
V. Polylogarithmic-time deterministic network decomposition and distributed derandomization , booktitle =. 2020 , xurl =. doi:10.1145/3357713.3384298 , timestamp =
-
[59]
Samir Khuller and Uzi Vishkin and Neal E. Young , title =. J. Algorithms , volume =. 1994 , xurl =. doi:10.1006/JAGM.1994.1036 , timestamp =
-
[60]
Reiter, Guy Golan-Gueta, and Ittai Abraham
Nir Bachrach and Keren Censor. Hardness of Distributed Optimization , booktitle =. 2019 , xurl =. doi:10.1145/3293611.3331597 , timestamp =
-
[61]
No sublogarithmic-time approximation scheme for bipartite vertex cover , journal =
Mika G. No sublogarithmic-time approximation scheme for bipartite vertex cover , journal =. 2014 , xurl =. doi:10.1007/S00446-013-0194-Z , timestamp =
-
[62]
Smaller Cuts, Higher Lower Bounds , journal =
Amir Abboud and Keren Censor. Smaller Cuts, Higher Lower Bounds , journal =. 2021 , xurl =. doi:10.1145/3469834 , timestamp =
-
[63]
On the complexity of local distributed graph problems , booktitle =
Mohsen Ghaffari and Fabian Kuhn and Yannic Maus , xeditor =. On the complexity of local distributed graph problems , booktitle =. 2017 , xurl =. doi:10.1145/3055399.3055471 , timestamp =
-
[64]
What cannot be computed locally! , booktitle =
Fabian Kuhn and Thomas Moscibroda and Roger Wattenhofer , xeditor =. What cannot be computed locally! , booktitle =. 2004 , xurl =. doi:10.1145/1011767.1011811 , timestamp =
-
[65]
Salwa Faour and Marc Fuchs and Fabian Kuhn , xeditor =. Distributed. 25th International Conference on Principles of Distributed Systems,. 2021 , xurl =. doi:10.4230/LIPICS.OPODIS.2021.17 , timestamp =
-
[66]
Approximating Bipartite Minimum Vertex Cover in the
Salwa Faour and Fabian Kuhn , xeditor =. Approximating Bipartite Minimum Vertex Cover in the. 24th International Conference on Principles of Distributed Systems,. 2020 , xurl =. doi:10.4230/LIPICS.OPODIS.2020.29 , timestamp =
-
[67]
Distributed Vertex Cover Reconfiguration , booktitle =
Keren Censor. Distributed Vertex Cover Reconfiguration , booktitle =. 2022 , xurl =. doi:10.4230/LIPICS.ITCS.2022.36 , timestamp =
-
[68]
Reuven Bar. J. 2017 , xurl =. doi:10.1145/3060294 , timestamp =
-
[69]
Finding Graph Matchings in Data Streams , booktitle =
Andrew McGregor , xeditor =. Finding Graph Matchings in Data Streams , booktitle =. 2005 , xurl =. doi:10.1007/11538462\_15 , timestamp =
-
[70]
Sepehr Assadi and S. Cliff Liu and Robert E. Tarjan , xeditor =. An Auction Algorithm for Bipartite Matching in Streaming and Massively Parallel Computation Models , booktitle =. 2021 , xurl =. doi:10.1137/1.9781611976496.18 , timestamp =
-
[71]
Adapting Local Sequential Algorithms to the Distributed Setting , booktitle =
Ken. Adapting Local Sequential Algorithms to the Distributed Setting , booktitle =. 2018 , xurl =. doi:10.4230/LIPICS.DISC.2018.35 , timestamp =
-
[72]
Kwok P. Choi , journal =. On the Medians of Gamma Distributions and an Equation of. 1994 , doi =
work page 1994
-
[73]
The Annals of Mathematical Statistics , number =
Wassily Hoeffding , title =. The Annals of Mathematical Statistics , number =. 1956 , doi =
work page 1956
-
[74]
Statistical Science , number =
Wenpin Tang and Fengmin Tang , title =. Statistical Science , number =. 2023 , doi =
work page 2023
-
[75]
Stochastic Vertex Cover with Few Queries , booktitle =
Soheil Behnezhad and Avrim Blum and Mahsa Derakhshan , xeditorx =. Stochastic Vertex Cover with Few Queries , booktitle =. 2022 , xurl =. doi:10.1137/1.9781611977073.73 , timestamp =
-
[76]
Stochastic Minimum Vertex Cover in General Graphs:
Mahsa Derakhshan and Naveen Durvasula and Nika Haghtalab , xeditorx =. Stochastic Minimum Vertex Cover in General Graphs:. 55th. 2023 , xurl =. doi:10.1145/3564246.3585230 , timestamp =
-
[77]
Data structures meet cryptography: 3SUM with preprocessing
Soheil Behnezhad and Mahsa Derakhshan and MohammadTaghi Hajiaghayi , xeditorx =. Stochastic matching with few queries: (1-. 52nd. 2020 , xurl =. doi:10.1145/3357713.3384340 , timestamp =
-
[78]
Krzysztof Onak and Dana Ron and Michal Rosen and Ronitt Rubinfeld , xeditorx =. A near-optimal sublinear-time algorithm for approximating the minimum vertex cover size , booktitle =. 2012 , xurl =. doi:10.1137/1.9781611973099.88 , timestamp =
-
[79]
Michal Parnas and Dana Ron , title =. Theor. Comput. Sci. , volume =. 2007 , xurl =. doi:10.1016/J.TCS.2007.04.040 , timestamp =
-
[80]
In: Proceed- ings of the Forty-First Annual ACM Symposium on Theory of Computing
Yuichi Yoshida and Masaki Yamamoto and Hiro Ito , xeditor =. An improved constant-time approximation algorithm for maximum matchings , booktitle =. 2009 , xurl =. doi:10.1145/1536414.1536447 , timestamp =
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.