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Documents authored by Tzamos, Christos


Document
APPROX
Approximating Pandora’s Box with Correlations

Authors: Shuchi Chawla, Evangelia Gergatsouli, Jeremy McMahan, and Christos Tzamos

Published in: LIPIcs, Volume 275, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)


Abstract
We revisit the classic Pandora’s Box (PB) problem under correlated distributions on the box values. Recent work of [Shuchi Chawla et al., 2020] obtained constant approximate algorithms for a restricted class of policies for the problem that visit boxes in a fixed order. In this work, we study the complexity of approximating the optimal policy which may adaptively choose which box to visit next based on the values seen so far. Our main result establishes an approximation-preserving equivalence of PB to the well studied Uniform Decision Tree (UDT) problem from stochastic optimization and a variant of the Min-Sum Set Cover (MSSC_f) problem. For distributions of support m, UDT admits a log m approximation, and while a constant factor approximation in polynomial time is a long-standing open problem, constant factor approximations are achievable in subexponential time [Ray Li et al., 2020]. Our main result implies that the same properties hold for PB and MSSC_f. We also study the case where the distribution over values is given more succinctly as a mixture of m product distributions. This problem is again related to a noisy variant of the Optimal Decision Tree which is significantly more challenging. We give a constant-factor approximation that runs in time n^Õ(m²/ε²) when the mixture components on every box are either identical or separated in TV distance by ε.

Cite as

Shuchi Chawla, Evangelia Gergatsouli, Jeremy McMahan, and Christos Tzamos. Approximating Pandora’s Box with Correlations. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 275, pp. 26:1-26:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{chawla_et_al:LIPIcs.APPROX/RANDOM.2023.26,
  author =	{Chawla, Shuchi and Gergatsouli, Evangelia and McMahan, Jeremy and Tzamos, Christos},
  title =	{{Approximating Pandora’s Box with Correlations}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)},
  pages =	{26:1--26:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-296-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{275},
  editor =	{Megow, Nicole and Smith, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2023.26},
  URN =		{urn:nbn:de:0030-drops-188519},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2023.26},
  annote =	{Keywords: Pandora’s Box, Min Sum Set Cover, stochastic optimization, approximation preserving reduction}
}
Document
Graph Connectivity with Noisy Queries

Authors: Dimitris Fotakis, Evangelia Gergatsouli, Charilaos Pipis, Miltiadis Stouras, and Christos Tzamos

Published in: LIPIcs, Volume 272, 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)


Abstract
Graph connectivity is a fundamental combinatorial optimization problem that arises in many practical applications, where usually a spanning subgraph of a network is used for its operation. However, in the real world, links may fail unexpectedly deeming the networks non-operational, while checking whether a link is damaged is costly and possibly erroneous. After an event that has damaged an arbitrary subset of the edges, the network operator must find a spanning tree of the network using non-damaged edges by making as few checks as possible. Motivated by such questions, we study the problem of finding a spanning tree in a network, when we only have access to noisy queries of the form "Does edge e exist?". We design efficient algorithms, even when edges fail adversarially, for all possible error regimes; 2-sided error (where any answer might be erroneous), false positives (where "no" answers are always correct) and false negatives (where "yes" answers are always correct). In the first two regimes we provide efficient algorithms and give matching lower bounds for general graphs. In the False Negative case we design efficient algorithms for large interesting families of graphs (e.g. bounded treewidth, sparse). Using the previous results, we provide tight algorithms for the practically useful family of planar graphs in all error regimes.

Cite as

Dimitris Fotakis, Evangelia Gergatsouli, Charilaos Pipis, Miltiadis Stouras, and Christos Tzamos. Graph Connectivity with Noisy Queries. In 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 272, pp. 47:1-47:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{fotakis_et_al:LIPIcs.MFCS.2023.47,
  author =	{Fotakis, Dimitris and Gergatsouli, Evangelia and Pipis, Charilaos and Stouras, Miltiadis and Tzamos, Christos},
  title =	{{Graph Connectivity with Noisy Queries}},
  booktitle =	{48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)},
  pages =	{47:1--47:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-292-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{272},
  editor =	{Leroux, J\'{e}r\^{o}me and Lombardy, Sylvain and Peleg, David},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2023.47},
  URN =		{urn:nbn:de:0030-drops-185810},
  doi =		{10.4230/LIPIcs.MFCS.2023.47},
  annote =	{Keywords: algorithms under uncertainty, graph connectivity, spanning tree, noisy queries, online algorithms, stochastic optimization}
}
Document
Track A: Algorithms, Complexity and Games
Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms

Authors: Kyriakos Axiotis and Christos Tzamos

Published in: LIPIcs, Volume 132, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019)


Abstract
One of the most fundamental problems in Computer Science is the Knapsack problem. Given a set of n items with different weights and values, it asks to pick the most valuable subset whose total weight is below a capacity threshold T. Despite its wide applicability in various areas in Computer Science, Operations Research, and Finance, the best known running time for the problem is O(T n). The main result of our work is an improved algorithm running in time O(TD), where D is the number of distinct weights. Previously, faster runtimes for Knapsack were only possible when both weights and values are bounded by M and V respectively, running in time O(nMV) [Pisinger, 1999]. In comparison, our algorithm implies a bound of O(n M^2) without any dependence on V, or O(n V^2) without any dependence on M. Additionally, for the unbounded Knapsack problem, we provide an algorithm running in time O(M^2) or O(V^2). Both our algorithms match recent conditional lower bounds shown for the Knapsack problem [Marek Cygan et al., 2017; Marvin Künnemann et al., 2017]. We also initiate a systematic study of general capacitated dynamic programming, of which Knapsack is a core problem. This problem asks to compute the maximum weight path of length k in an edge- or node-weighted directed acyclic graph. In a graph with m edges, these problems are solvable by dynamic programming in time O(k m), and we explore under which conditions the dependence on k can be eliminated. We identify large classes of graphs where this is possible and apply our results to obtain linear time algorithms for the problem of k-sparse Delta-separated sequences. The main technical innovation behind our results is identifying and exploiting concavity that appears in relaxations and subproblems of the tasks we consider.

Cite as

Kyriakos Axiotis and Christos Tzamos. Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms. In 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 132, pp. 19:1-19:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@InProceedings{axiotis_et_al:LIPIcs.ICALP.2019.19,
  author =	{Axiotis, Kyriakos and Tzamos, Christos},
  title =	{{Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms}},
  booktitle =	{46th International Colloquium on Automata, Languages, and Programming (ICALP 2019)},
  pages =	{19:1--19:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-109-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{132},
  editor =	{Baier, Christel and Chatzigiannakis, Ioannis and Flocchini, Paola and Leonardi, Stefano},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2019.19},
  URN =		{urn:nbn:de:0030-drops-105952},
  doi =		{10.4230/LIPIcs.ICALP.2019.19},
  annote =	{Keywords: Knapsack, Fine-Grained Complexity, Dynamic Programming}
}
Document
Tight Hardness Results for Maximum Weight Rectangles

Authors: Arturs Backurs, Nishanth Dikkala, and Christos Tzamos

Published in: LIPIcs, Volume 55, 43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016)


Abstract
Given n weighted points (positive or negative) in d dimensions, what is the axis-aligned box which maximizes the total weight of the points it contains? The best known algorithm for this problem is based on a reduction to a related problem, the Weighted Depth problem [Chan, FOCS, 2013], and runs in time O(n^d). It was conjectured [Barbay et al., CCCG, 2013] that this runtime is tight up to subpolynomial factors. We answer this conjecture affirmatively by providing a matching conditional lower bound. We also provide conditional lower bounds for the special case when points are arranged in a grid (a well studied problem known as Maximum Subarray problem) as well as for other related problems. All our lower bounds are based on assumptions that the best known algorithms for the All-Pairs Shortest Paths problem (APSP) and for the Max-Weight k-Clique problem in edge-weighted graphs are essentially optimal.

Cite as

Arturs Backurs, Nishanth Dikkala, and Christos Tzamos. Tight Hardness Results for Maximum Weight Rectangles. In 43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 55, pp. 81:1-81:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{backurs_et_al:LIPIcs.ICALP.2016.81,
  author =	{Backurs, Arturs and Dikkala, Nishanth and Tzamos, Christos},
  title =	{{Tight Hardness Results for Maximum Weight Rectangles}},
  booktitle =	{43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016)},
  pages =	{81:1--81:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-013-2},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{55},
  editor =	{Chatzigiannakis, Ioannis and Mitzenmacher, Michael and Rabani, Yuval and Sangiorgi, Davide},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2016.81},
  URN =		{urn:nbn:de:0030-drops-62040},
  doi =		{10.4230/LIPIcs.ICALP.2016.81},
  annote =	{Keywords: Maximum Rectangles, Hardness in P}
}
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