We study the query complexity on slices of Boolean functions. Among other results we show that there exists a Boolean function for which we need to query all but 7 input bits to compute its value, even if we know befo...
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We study the query complexity on slices of Boolean functions. Among other results we show that there exists a Boolean function for which we need to query all but 7 input bits to compute its value, even if we know beforehand that the number of 0's and 1's in the input are the same, i.e., when our input is from the middle slice. This answers a question of Byramji. Our proof is non-constructive, but we also propose a concrete candidate function that might have the above property. Our results are related to certain natural discrepancy type questions that, somewhat surprisingly, have not been studied before. (c) 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).
In this paper,we consider the exact quantum query complexity of two fundamental symmetric functions.1)MOD_(m)^(n),which calculates the Hamming weight of an-bit string modulo;2)EXACT_(k,l)^(n),which determines if the H...
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In this paper,we consider the exact quantum query complexity of two fundamental symmetric functions.1)MOD_(m)^(n),which calculates the Hamming weight of an-bit string modulo;2)EXACT_(k,l)^(n),which determines if the Hamming weight of an-bit string is exactly k or *** these two symmetric functions have received considerable attention,their exact quantum query complexities have not been fully ***,our results are as follows:1)We design an optimal quantum query algorithm to compute MOD_(m)^(n)exactly and thus provide a tight characterization of its exact quantum query complexity,which settles a previous *** on this algorithm,we demonstrate that a broad class of symmetric functions is not evasive in the quantum model,i.e.,there exist quantum algorithms to compute these functions exactly when the number of queries is less than their input size.2)By proposing a quantum algorithm that utilizes the minimum number of queries to compute EXACT_(k,l)^(n)exactly for some specific values of k and l,we give a tight characterization of its exact quantum query complexity in these scenarios.
In this work, we consider the Submodular Maximization under Knapsack (SMK) constraint problem over the ground set of size n. The problem recently attracted a lot of attention due to its applications in various domains...
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In this work, we consider the Submodular Maximization under Knapsack (SMK) constraint problem over the ground set of size n. The problem recently attracted a lot of attention due to its applications in various domains of combinatorial optimization, artificial intelligence, and machine learning. We improve the approximation factor of the fastest deterministic algorithm from 6+& varepsilon;to 5+& varepsilon;while keeping the best query complexity of O(n), where & varepsilon;>0 is a constant parameter. Our technique is based on optimizing the performance of two components: the threshold greedy subroutine and the building of two disjoint sets as candidate solutions. Besides, by carefully analyzing the cost of candidate solutions, we obtain a tighter approximation factor.
Watrous conjectured that the randomized and quantum query complexities of symmetric functions are polynomially equivalent, which was resolved by Aaronson & Ambainis (2014) and was later improved by Chailloux (2019...
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Watrous conjectured that the randomized and quantum query complexities of symmetric functions are polynomially equivalent, which was resolved by Aaronson & Ambainis (2014) and was later improved by Chailloux (2019) and Ben-David et al. (2020). This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to 1/2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1/2$$\end{document}. Our contributions include the following: We analyze the optimal success probabilities of quantum and randomized query algorithms of two fundamental partial symmetric Boolean functions given a fixed number of *** establish that for any total symmetric Boolean function f\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document}, if a quantum algorithm uses T\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T$$\end{document} queries to compute f\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document} with success probability 1/2+beta\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1/2
This paper investigates how many queries to k-membership comparable sets are needed in order to decide all (k + 1)-membership comparable sets. For k greater than or equal to 2 this query complexity is at least linear ...
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This paper investigates how many queries to k-membership comparable sets are needed in order to decide all (k + 1)-membership comparable sets. For k greater than or equal to 2 this query complexity is at least linear and at most cubic. As a corollary, we obtain that more languages are O(log n)-membership comparable than truth-table reducible to P-selective sets. (C) 2003 Elsevier Science B.V. All rights reserved.
We study variants of Mastermind, a popular board game in which the objective is sequence reconstruction. In this two-player game, the so-called codemaker constructs a hidden sequence H = (h(1), h(2), ... , h(n)) of co...
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We study variants of Mastermind, a popular board game in which the objective is sequence reconstruction. In this two-player game, the so-called codemaker constructs a hidden sequence H = (h(1), h(2), ... , h(n)) of colors selected from an alphabet A = {1, 2, ... , k} (i.e., h(i) is an element of A for all i is an element of{1, 2, ... , n}). The game then proceeds in turns, each of which consists of two parts: in turn t, the second player (the codebreaker) first submits a query sequence Q(t) = (q(1), q(2), ... , q(n)) with q(i) is an element of A for all i, and second receives feedback Delta(Q(t), H), where Delta is some agreed-upon function of distance between two sequences with n components. The game terminates when the codebreaker has determined the value of H, and the codebreaker seeks to end the game in as few turns as possible. Throughout we let f(n, k) denote the smallest integer such that the codebreaker can determine any H in f(n, k) turns. We prove three main results: First, when H is known to be a permutation of {1, 2, ... , n}, we prove that f(n, n) >= n - log log n for all sufficiently large n. Second, we show that Knuth's Minimax algorithm identifies any H in at most nk queries. Third, when feedback is not received until all queries have been submitted, we show that f(n, k) = Omega(n log k). (C) 2017 Elsevier B.V. All rights reserved.
Consider a regression problem where the learner is given a large collection of d-dimensional data points, but can only query a small subset of the real-valued labels. How many queries are needed to obtain a 1+ epsilon...
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Consider a regression problem where the learner is given a large collection of d-dimensional data points, but can only query a small subset of the real-valued labels. How many queries are needed to obtain a 1+ epsilon relative error approximation of the optimum? While this problem has been extensively studied for least squares regression, little is known for other losses. An important example is least absolute deviation regression (l(1) regression) which enjoys superior robustness to outliers compared to least squares. We develop a new framework for analyzing importance sampling methods in regression problems, which enables us to show that the query complexity of least absolute deviation regression is Theta(d/epsilon(2)) up to logarithmic factors. We further extend our techniques to show the first bounds on the query complexity for any l(p) loss with p is an element of (1, 2). As a key novelty in our analysis, we introduce the notion of robust uniform convergence, which is a new approximation guarantee for the empirical loss. While it is inspired by uniform convergence in statistical learning, our approach additionally incorporates a correction term to avoid unnecessary variance due to outliers. This can be viewed as a new connection between statistical learning theory and variance reduction techniques in stochastic optimization, which should be of independent interest.
We study the query complexity of approximate notions of Nash equilibrium in games with a large number of players n and a constant number of actions m. Our main result states that even for constant epsilon, the query c...
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ISBN:
(纸本)9781450327107
We study the query complexity of approximate notions of Nash equilibrium in games with a large number of players n and a constant number of actions m. Our main result states that even for constant epsilon, the query complexity of an epsilon-well-supported Nash equilibrium is exponential in n.
Inspired by the Elitzur-Vaidman bomb testing problem (1993), we introduce a new query complexity model, which we call bomb query complexity, B(f). We investigate its relationship with the usual quantum query complexit...
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Inspired by the Elitzur-Vaidman bomb testing problem (1993), we introduce a new query complexity model, which we call bomb query complexity, B(f). We investigate its relationship with the usual quantum query complexity Q(f), and show that B(f) = Theta(Q(f)(2)). This result gives a new method to derive upper bounds on quantum query complexity: we give a method of finding bomb query algorithms from classical algorithms, which then provide non-constructive upper bounds on Q(f) = Theta(root B(f)). Subsequently, we were able to give explicit quantum algorithms matching our new bounds. We apply this method to the single-source shortest paths problem on unweighted graphs, obtaining an algorithm with O(n(1.5)) quantum query complexity, improving the best known algorithm of O(n(1.5)logn) (Durr et al. 2006, Furrow 2008). Applying this method to the maximum bipartite matching problem gives an algorithm with O(n(1.75)) quantum query complexity, improving the best known (trivial) O(n(2)) upper bound.
We prove a very general lower bound technique for quantum and randomized query complexity that is easy to prove as well as to apply. To achieve this, we introduce the use of Kolmogorov complexity to query complexity. ...
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We prove a very general lower bound technique for quantum and randomized query complexity that is easy to prove as well as to apply. To achieve this, we introduce the use of Kolmogorov complexity to query complexity. Our technique generalizes the weighted and unweighted methods of Ambainis and the spectral method of Barnum, Saks, and Szegedy. As an immediate consequence of our main theorem, it can be shown that adversary methods can only prove lower bounds for Boolean functions f in O(min(root nC(0)(f), root nC(1)(f))), where C-0, C-1 is the certificate complexity and n is the size of the input.
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