Simple Dynamic Spanners with Near-optimal Recourse against an Adaptive Adversary

Designing dynamic algorithms against an adaptive adversary whose performance match the ones assuming an oblivious adversary is a major research program in the field of dynamic graph algorithms. One of the prominent examples whose oblivious-vs-adaptive gap remains maximally large is the fully dynamic spanner problem; there exist algorithms assuming an oblivious adversary with near-optimal size-stretch trade-off using only polylog( n ) update time [Baswana, Khurana, and Sarkar TALG’12; Forster and Goranci STOC’19; Bernstein, Forster, and Henzinger SODA’20], while against an adaptive adversary, even when we allow infinite time and only count recourse (i.e. the number of edge changes per update in the maintained spanner), all previous algorithms with stretch at most log 5 ( n ) require at least Ω( n ) amortized recourse [Ausiello, Franciosa, and Italiano ESA’05]. In this paper, we completely close this gap with respect to recourse by showing algorithms against an adaptive adversary with near-optimal size-stretch trade-off and recourse. More precisely, for any k ≥ 1, our algorithm maintains a (2 k − 1)-spanner of size O ( n 1+1 /k log n ) with O (log n ) amortized recourse, which is optimal in all parameters up to a O (log n ) factor. As a step toward algorithms with small update time (not just recourse), we show another algorithm that maintains a 3-spanner of size ˜ O ( n 1 . 5 ) with polylog( n ) amortized recourse and simultaneously ˜ O ( √ n ) worst-case update time.

[1]  Peter Kiss,et al.  Deterministic Dynamic Matching in Worst-Case Update Time , 2021, ITCS.

[2]  Vladimir Braverman,et al.  Adversarial Robustness of Streaming Algorithms through Importance Sampling , 2021, NeurIPS.

[3]  Julia Chuzhoy,et al.  Decremental all-pairs shortest paths in deterministic near-linear time , 2021, STOC.

[4]  Jason Li,et al.  Deterministic mincut in almost-linear time , 2021, STOC.

[5]  Seth Neel,et al.  Adaptive Machine Unlearning , 2021, NeurIPS.

[6]  Tianyi Zhang Faster Cut-Equivalent Trees in Simple Graphs , 2021, ICALP.

[7]  Robert Krauthgamer,et al.  APMF < APSP? Gomory-Hu Tree for Unweighted Graphs in Almost-Quadratic Time* , 2021, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS).

[8]  Debmalya Panigrahi,et al.  A Nearly Optimal All-Pairs Min-Cuts Algorithm in Simple Graphs , 2021, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS).

[9]  Thatchaphol Saranurak,et al.  Deterministic Weighted Expander Decomposition in Almost-linear Time , 2021, ArXiv.

[10]  Sayan Bhattacharya,et al.  Deterministic Rounding of Dynamic Fractional Matchings , 2021, ICALP.

[11]  Haim Kaplan,et al.  Separating Adaptive Streaming from Oblivious Streaming , 2021, ArXiv.

[12]  Noga Alon,et al.  Adversarial laws of large numbers and optimal regret in online classification , 2021, STOC.

[13]  Thatchaphol Saranurak,et al.  Deterministic Decremental SSSP and Approximate Min-Cost Flow in Almost-Linear Time , 2021, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS).

[14]  Yin Tat Lee,et al.  Minimum cost flows, MDPs, and ℓ1-regression in nearly linear time for dense instances , 2021, STOC.

[15]  David P. Woodruff,et al.  Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators , 2020, 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS).

[16]  Fabrizio Grandoni,et al.  Online Edge Coloring Algorithms via the Nibble Method , 2020, SODA.

[17]  Thatchaphol Saranurak,et al.  Deterministic Algorithms for Decremental Shortest Paths via Layered Core Decomposition , 2020, SODA.

[18]  Richard Peng,et al.  Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs , 2020, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

[19]  Anupam Gupta,et al.  Fully-Dynamic Submodular Cover with Bounded Recourse , 2020, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

[20]  Thatchaphol Saranurak,et al.  The Expander Hierarchy and its Applications to Dynamic Graph Algorithms , 2020, SODA.

[21]  Richard Peng,et al.  Fast Dynamic Cuts, Distances and Effective Resistances via Vertex Sparsifiers , 2020, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

[22]  Thatchaphol Saranurak,et al.  Fully-Dynamic Graph Sparsifiers Against an Adaptive Adversary , 2020, ICALP.

[23]  Haim Kaplan,et al.  Adversarially Robust Streaming Algorithms via Differential Privacy , 2020, NeurIPS.

[24]  David P. Woodruff,et al.  A Framework for Adversarially Robust Streaming Algorithms , 2020, SIGMOD Rec..

[25]  Virginia Vassilevska Williams,et al.  New algorithms and hardness for incremental single-source shortest paths in directed graphs , 2020, STOC.

[26]  Christian Wulff-Nilsen,et al.  Decremental SSSP in Weighted Digraphs: Faster and Against an Adaptive Adversary , 2020, SODA.

[27]  Christian Wulff-Nilsen,et al.  Deterministic Algorithms for Decremental Approximate Shortest Paths: Faster and Simpler , 2020, SODA.

[28]  David Wajc,et al.  Rounding dynamic matchings against an adaptive adversary , 2019, STOC.

[29]  E. Rotenberg,et al.  Fully-dynamic planarity testing in polylogarithmic time , 2019, STOC.

[30]  Jacob Holm,et al.  Worst-Case Polylog Incremental SPQR-trees: Embeddings, Planarity, and Triconnectivity , 2019, SODA.

[31]  Richard Peng,et al.  A Deterministic Algorithm for Balanced Cut with Applications to Dynamic Connectivity, Flows, and Beyond , 2019, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

[32]  S. Chechik,et al.  Fully Dynamic Maximal Independent Set in Expected Poly-Log Update Time , 2019, 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS).

[33]  Soheil Behnezhad,et al.  Fully Dynamic Maximal Independent Set with Polylogarithmic Update Time , 2019, 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS).

[34]  Julia Chuzhoy,et al.  A new algorithm for decremental single-source shortest paths with applications to vertex-capacitated flow and cut problems , 2019, STOC.

[35]  Christian Wulff-Nilsen,et al.  Decremental strongly-connected components and single-source reachability in near-linear time , 2019, STOC.

[36]  Thatchaphol Saranurak,et al.  Expander Decomposition and Pruning: Faster, Stronger, and Simpler , 2018, SODA.

[37]  Monika Henzinger,et al.  A Deamortization Approach for Dynamic Spanner and Dynamic Maximal Matching , 2018, SODA.

[38]  Janardhan Kulkarni,et al.  Deterministically Maintaining a (2+ε)-Approximate Minimum Vertex Cover in O(1/ε2) Amortized Update Time , 2018, SODA.

[39]  Sebastian Krinninger,et al.  Dynamic low-stretch trees via dynamic low-diameter decompositions , 2018, STOC.

[40]  Benjamin Doerr,et al.  Probabilistic Tools for the Analysis of Randomized Optimization Heuristics , 2018, Theory of Evolutionary Computation.

[41]  Shiri Chechik,et al.  Incremental Topological Sort and Cycle Detection in Expected Total Time , 2018, SODA.

[42]  Christian Wulff-Nilsen,et al.  Dynamic Minimum Spanning Forest with Subpolynomial Worst-Case Update Time , 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

[43]  Merav Parter,et al.  Improved Deterministic Distributed Construction of Spanners , 2017, DISC.

[44]  Thatchaphol Saranurak,et al.  Dynamic spanning forest with worst-case update time: adaptive, Las Vegas, and O(n1/2 - ε)-time , 2017, STOC.

[45]  Aaron Bernstein,et al.  Deterministic Partially Dynamic Single Source Shortest Paths in Weighted Graphs , 2017, ICALP.

[46]  Thomas Steinke,et al.  Tight Lower Bounds for Differentially Private Selection , 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

[47]  Shiri Chechik,et al.  Deterministic Partially Dynamic Single Source Shortest Paths for Sparse Graphs , 2017, SODA.

[48]  Monika Henzinger,et al.  Fully Dynamic Approximate Maximum Matching and Minimum Vertex Cover in O(log3 n) Worst Case Update Time , 2017, SODA.

[49]  Christian Wulff-Nilsen,et al.  Fully-dynamic minimum spanning forest with improved worst-case update time , 2016, STOC.

[50]  Sebastian Krinninger,et al.  Fully Dynamic Spanners with Worst-Case Update Time , 2016, ESA.

[51]  Shiri Chechik,et al.  Deterministic decremental single source shortest paths: beyond the o(mn) bound , 2016, STOC.

[52]  Monika Henzinger,et al.  New deterministic approximation algorithms for fully dynamic matching , 2016, STOC.

[53]  Richard Peng,et al.  On Fully Dynamic Graph Sparsifiers , 2016, 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS).

[54]  Raef Bassily,et al.  Algorithmic stability for adaptive data analysis , 2015, STOC.

[55]  Stefan Schmid,et al.  Dynamic Balanced Graph Partitioning , 2015, SIAM J. Discret. Math..

[56]  Keren Censor-Hillel,et al.  Optimal Dynamic Distributed MIS , 2015, PODC.

[57]  Surender Baswana,et al.  Dynamic DFS in Undirected Graphs: breaking the O(m) barrier , 2015, SODA.

[58]  Giuseppe F. Italiano,et al.  Deterministic Fully Dynamic Data Structures for Vertex Cover and Matching , 2014, SODA.

[59]  Toniann Pitassi,et al.  Preserving Statistical Validity in Adaptive Data Analysis , 2014, STOC.

[60]  Jonathan Ullman,et al.  Preventing False Discovery in Interactive Data Analysis Is Hard , 2014, 2014 IEEE 55th Annual Symposium on Foundations of Computer Science.

[61]  Amit Kumar,et al.  Maintaining Assignments Online: Matching, Scheduling, and Flows , 2014, SODA.

[62]  Jan Vondrák,et al.  Fast algorithms for maximizing submodular functions , 2014, SODA.

[63]  Amit Kumar,et al.  Online Steiner Tree with Deletions , 2013, SODA.

[64]  Soumojit Sarkar,et al.  Fully dynamic randomized algorithms for graph spanners , 2012, TALG.

[65]  Michael Elkin,et al.  Streaming and fully dynamic centralized algorithms for constructing and maintaining sparse spanners , 2007, TALG.

[66]  Giuseppe F. Italiano,et al.  Small Stretch Spanners on Dynamic Graphs , 2005, J. Graph Algorithms Appl..

[67]  Mikkel Thorup,et al.  Worst-case update times for fully-dynamic all-pairs shortest paths , 2005, STOC '05.

[68]  Mikkel Thorup,et al.  Poly-logarithmic deterministic fully-dynamic algorithms for connectivity, minimum spanning tree, 2-edge, and biconnectivity , 2001, JACM.

[69]  Lisa Fleischer,et al.  Approximating fractional multicommodity flow independent of the number of commodities , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[70]  Jochen Könemann,et al.  Faster and simpler algorithms for multicommodity flow and other fractional packing problems , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[71]  David P. Dobkin,et al.  On sparse spanners of weighted graphs , 1993, Discret. Comput. Geom..

[72]  Rephael Wenger,et al.  Extremal graphs with no C4's, C6's, or C10's , 1991, J. Comb. Theory, Ser. B.

[73]  Shiri Chechik,et al.  Dynamic Low-Stretch Spanning Trees in Subpolynomial Time , 2020, SODA.