4 Search Results for "Grossman, Tomer"


Document
From Donkeys to Kings in Tournaments

Authors: Amir Abboud, Tomer Grossman, Moni Naor, and Tomer Solomon

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)


Abstract
A tournament is an orientation of a complete graph. A vertex that can reach every other vertex within two steps is called a king. We study the complexity of finding k kings in a tournament graph. We show that the randomized query complexity of finding k ≤ 3 kings is O(n), and for the deterministic case it takes the same amount of queries (up to a constant) as finding a single king (the best known deterministic algorithm makes O(n^{3/2}) queries). On the other hand, we show that finding k ≥ 4 kings requires Ω(n²) queries, even in the randomized case. We consider the RAM model for k ≥ 4. We show an algorithm that finds k kings in time O(kn²), which is optimal for constant values of k. Alternatively, one can also find k ≥ 4 kings in time n^{ω} (the time for matrix multiplication). We provide evidence that this is optimal for large k by suggesting a fine-grained reduction from a variant of the triangle detection problem.

Cite as

Amir Abboud, Tomer Grossman, Moni Naor, and Tomer Solomon. From Donkeys to Kings in Tournaments. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 3:1-3:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{abboud_et_al:LIPIcs.ESA.2024.3,
  author =	{Abboud, Amir and Grossman, Tomer and Naor, Moni and Solomon, Tomer},
  title =	{{From Donkeys to Kings in Tournaments}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{3:1--3:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.3},
  URN =		{urn:nbn:de:0030-drops-210740},
  doi =		{10.4230/LIPIcs.ESA.2024.3},
  annote =	{Keywords: Tournament Graphs, Kings, Query Complexity, Fine Grained Complexity}
}
Document
Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping

Authors: Kevin Gonyop Kim, Tiffany C.K. Kwok, Sailin Zhong, Peter Kiefer, and Martin Raubal

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)


Abstract
Sketch mapping is a research technique that has been widely used to study what people think about the spatial layout of an environment. One of the limitations of the current practice of sketch mapping is that the interface (a pen on paper or digital tablets) forces people to draw on 2D surfaces even when the information to be represented is 3D. For the purpose of studying the 3D aspect of spatial understanding, the recent advancements in extended reality (XR) technologies including virtual reality, augmented reality, and mixed reality are interesting as they provide novel ways to create 3D sketches. In this paper, we investigate how the concept of 3D sketch mapping using XR is perceived by users and explore its potential feasibility and use cases. For this, we conducted semi-structured interviews with 27 participants from three domains: aviation, architecture, and wayfinding. Our findings show that the concept is well-perceived as an intuitive way to externalize the 3D aspect of spatial information, and it has the potential to be a research tool for human cognition research as well as a practical tool that can provide added value in different professional activities.

Cite as

Kevin Gonyop Kim, Tiffany C.K. Kwok, Sailin Zhong, Peter Kiefer, and Martin Raubal. Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 3:1-3:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{kim_et_al:LIPIcs.COSIT.2024.3,
  author =	{Kim, Kevin Gonyop and Kwok, Tiffany C.K. and Zhong, Sailin and Kiefer, Peter and Raubal, Martin},
  title =	{{Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{3:1--3:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.3},
  URN =		{urn:nbn:de:0030-drops-208186},
  doi =		{10.4230/LIPIcs.COSIT.2024.3},
  annote =	{Keywords: Sketch maps, spatial understanding, 3D sketching, extended reality, use cases, interviews}
}
Document
Keep That Card in Mind: Card Guessing with Limited Memory

Authors: Boaz Menuhin and Moni Naor

Published in: LIPIcs, Volume 215, 13th Innovations in Theoretical Computer Science Conference (ITCS 2022)


Abstract
A card guessing game is played between two players, Guesser and Dealer. At the beginning of the game, the Dealer holds a deck of n cards (labeled 1, ..., n). For n turns, the Dealer draws a card from the deck, the Guesser guesses which card was drawn, and then the card is discarded from the deck. The Guesser receives a point for each correctly guessed card. With perfect memory, a Guesser can keep track of all cards that were played so far and pick at random a card that has not appeared so far, yielding in expectation ln n correct guesses, regardless of how the Dealer arranges the deck. With no memory, the best a Guesser can do will result in a single guess in expectation. We consider the case of a memory bounded Guesser that has m < n memory bits. We show that the performance of such a memory bounded Guesser depends much on the behavior of the Dealer. In more detail, we show that there is a gap between the static case, where the Dealer draws cards from a properly shuffled deck or a prearranged one, and the adaptive case, where the Dealer draws cards thoughtfully, in an adversarial manner. Specifically: 1) We show a Guesser with O(log² n) memory bits that scores a near optimal result against any static Dealer. 2) We show that no Guesser with m bits of memory can score better than O(√m) correct guesses against a random Dealer, thus, no Guesser can score better than min {√m, ln n}, i.e., the above Guesser is optimal. 3) We show an efficient adaptive Dealer against which no Guesser with m memory bits can make more than ln m + 2 ln log n + O(1) correct guesses in expectation. These results are (almost) tight, and we prove them using compression arguments that harness the guessing strategy for encoding.

Cite as

Boaz Menuhin and Moni Naor. Keep That Card in Mind: Card Guessing with Limited Memory. In 13th Innovations in Theoretical Computer Science Conference (ITCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 215, pp. 107:1-107:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{menuhin_et_al:LIPIcs.ITCS.2022.107,
  author =	{Menuhin, Boaz and Naor, Moni},
  title =	{{Keep That Card in Mind: Card Guessing with Limited Memory}},
  booktitle =	{13th Innovations in Theoretical Computer Science Conference (ITCS 2022)},
  pages =	{107:1--107:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-217-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{215},
  editor =	{Braverman, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2022.107},
  URN =		{urn:nbn:de:0030-drops-157039},
  doi =		{10.4230/LIPIcs.ITCS.2022.107},
  annote =	{Keywords: Adaptivity vs Non-adaptivity, Adversarial Robustness, Card Guessing, Compression Argument, Information Theory, Streaming Algorithms, Two Player Game}
}
Document
Instance Complexity and Unlabeled Certificates in the Decision Tree Model

Authors: Tomer Grossman, Ilan Komargodski, and Moni Naor

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


Abstract
Instance complexity is a measure of goodness of an algorithm in which the performance of one algorithm is compared to others per input. This is in sharp contrast to worst-case and average-case complexity measures, where the performance is compared either on the worst input or on an average one, respectively. We initiate the systematic study of instance complexity and optimality in the query model (a.k.a. the decision tree model). In this model, instance optimality of an algorithm for computing a function is the requirement that the complexity of an algorithm on any input is at most a constant factor larger than the complexity of the best correct algorithm. That is we compare the decision tree to one that receives a certificate and its complexity is measured only if the certificate is correct (but correctness should hold on any input). We study both deterministic and randomized decision trees and provide various characterizations and barriers for more general results. We introduce a new measure of complexity called unlabeled-certificate complexity, appropriate for graph properties and other functions with symmetries, where only information about the structure of the graph is known to the competing algorithm. More precisely, the certificate is some permutation of the input (rather than the input itself) and the correctness should be maintained even if the certificate is wrong. First we show that such an unlabeled certificate is sometimes very helpful in the worst-case. We then study instance optimality with respect to this measure of complexity, where an algorithm is said to be instance optimal if for every input it performs roughly as well as the best algorithm that is given an unlabeled certificate (but is correct on every input). We show that instance optimality depends on the group of permutations in consideration. Our proofs rely on techniques from hypothesis testing and analysis of random graphs.

Cite as

Tomer Grossman, Ilan Komargodski, and Moni Naor. Instance Complexity and Unlabeled Certificates in the Decision Tree Model. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 56:1-56:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{grossman_et_al:LIPIcs.ITCS.2020.56,
  author =	{Grossman, Tomer and Komargodski, Ilan and Naor, Moni},
  title =	{{Instance Complexity and Unlabeled Certificates in the Decision Tree Model}},
  booktitle =	{11th Innovations in Theoretical Computer Science Conference (ITCS 2020)},
  pages =	{56:1--56:38},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2020.56},
  URN =		{urn:nbn:de:0030-drops-117418},
  doi =		{10.4230/LIPIcs.ITCS.2020.56},
  annote =	{Keywords: decision tree complexity, instance complexity, instance optimality, query complexity, unlabeled certificates}
}
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