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Let $f:\{0,1\}^n \rightarrow \{0,1\}$ be a Boolean function. The certificate complexity $C(f)$ is a complexity measure that is quadratically tight for the zero-error randomized query complexity $R_0(f)$: $C(f) \leq R_0(f) \leq C(f)^2$. In…

Computational Complexity · Computer Science 2017-08-03 Dmitry Gavinsky , Rahul Jain , Hartmut Klauck , Srijita Kundu , Troy Lee , Miklos Santha , Swagato Sanyal , Jevgenijs Vihrovs

We describe a slightly sub-exponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomial-time algorithm for the case of parity functions that depend on only the first…

Machine Learning · Computer Science 2007-05-23 Avrim Blum , Adam Kalai , Hal Wasserman

We show that if G is a finite group and f is a {0,1}-valued function on G with Fourier algebra norm at most M then f may be computed by a coset decision tree (that is a decision tree in which at each vertex we query membership of a given…

Classical Analysis and ODEs · Mathematics 2019-11-11 Tom Sanders

We consider a probability distribution on the set of Boolean functions in n variables which is induced by random Boolean expressions. Such an expression is a random rooted plane tree where the internal vertices are labelled with connectives…

Combinatorics · Mathematics 2015-09-28 Antoine Genitrini , Bernhard Gittenberger , Veronika Kraus , Cécile Mailler

Equality and disjointness are two of the most studied problems in communication complexity. They have been studied for both classical and also quantum communication and for various models and modes of communication. Buhrman et al. [Buh98]…

Computational Complexity · Computer Science 2013-10-01 Jozef Gruska , Daowen Qiu , Shenggen Zheng

We consider the following communication problem: Alice and Bob each have some valuation functions $v_1(\cdot)$ and $v_2(\cdot)$ over subsets of $m$ items, and their goal is to partition the items into $S, \bar{S}$ in a way that maximizes…

Computer Science and Game Theory · Computer Science 2017-04-13 Mark Braverman , Jieming Mao , S. Matthew Weinberg

We show that any bounded integral function $f : A \times B \mapsto \{0,1, \dots, \Delta\}$ with rank $r$ has deterministic communication complexity $\Delta^{O(\Delta)} \cdot \sqrt{r} \cdot \log r$, where the rank of $f$ is defined to be the…

Discrete Mathematics · Computer Science 2024-03-22 Sally Dong , Thomas Rothvoss

In this report, we study the multiparty communication complexity problem of the multiparty equality function (MEQ): EQ(x_1,...,x_n) = 1 if x_1=...=x_n, and 0 otherwise. The input vector (x_1,...,x_n) is distributed among n>=2 nodes, with…

Information Theory · Computer Science 2010-10-27 Guanfeng Liang , Nitin Vaidya

Parys has recently proposed a quasi-polynomial version of Zielonka's recursive algorithm for solving parity games. In this brief note we suggest a variation of his algorithm that improves the complexity to meet the state-of-the-art…

Computer Science and Game Theory · Computer Science 2019-06-06 Karoliina Lehtinen , Sven Schewe , Dominik Wojtczak

We define an extension of parity from the integers to the rational numbers. Three parity classes are found -- even, odd and `none'. Using the 2-adic valuation, we partition the rationals into subgroups with a rich algebraic structure. The…

Number Theory · Mathematics 2022-05-03 Peter Lynch , Michael Mackey

Given a graph G, we investigate the question of determining the parity of the number of homomorphisms from G to some other fixed graph H. We conjecture that this problem exhibits a complexity dichotomy, such that all parity graph…

Computational Complexity · Computer Science 2013-09-17 John Faben , Mark Jerrum

We prove tight bounds of Theta(k log k) queries for non-adaptively testing whether a function f:{0,1}^n -> {0,1} is a k-parity or far from any k-parity. The lower bound combines a recent method of Blais, Brody and Matulef [BBM11] to get…

Computational Complexity · Computer Science 2013-07-04 Harry Buhrman , David Garcia-Soriano , Arie Matsliah , Ronald de Wolf

A decision tree recursively splits a feature space $\mathbb{R}^{d}$ and then assigns class labels based on the resulting partition. Decision trees have been part of the basic machine-learning toolkit for decades. A large body of work treats…

Communication complexity is the amount of communication needed to compute a function when the function inputs are distributed over multiple parties. In its simplest form, one-way communication complexity, Alice and Bob compute a function…

Computational Complexity · Computer Science 2023-05-24 Naresh Goud Boddu , Rahul Jain , Han-Hsuan Lin

We show that there exists a Boolean function $F$ which observes the following separations among deterministic query complexity $(D(F))$, randomized zero error query complexity $(R_0(F))$ and randomized one-sided error query complexity…

Computational Complexity · Computer Science 2015-06-25 Sagnik Mukhopadhyay , Swagato Sanyal

We initiate the study of the communication complexity of fair division with indivisible goods. We focus on some of the most well-studied fairness notions (envy-freeness, proportionality, and approximations thereof) and valuation classes…

Computer Science and Game Theory · Computer Science 2020-03-25 Benjamin Plaut , Tim Roughgarden

Decision trees are one of the most fundamental computational models for computing Boolean functions $f : \{0, 1\}^n \mapsto \{0, 1\}$. It is well-known that the depth and size of decision trees are closely related to time and number of…

Computational Complexity · Computer Science 2025-01-03 Deepu Benson , Balagopal Komarath , Jayalal Sarma , Nalli Sai Soumya

The quantum version of communication complexity allows the two communicating parties to exchange qubits and/or to make use of prior entanglement (shared EPR-pairs). Some lower bound techniques are available for qubit communication…

Computational Complexity · Computer Science 2007-05-23 Harry Buhrman , Ronald de Wolf

We consider the class of functions whose value depends only on the intersection of the input X_1,X_2, ..., X_t; that is, for each F in this class there is an f_F: 2^{[n]} \to {0,1}, such that F(X_1,X_2, ..., X_t) = f_F(X_1 \cap X_2 \cap ...…

Quantum Physics · Physics 2007-05-23 Rahul Jain , Jaikumar Radhakrishnan , Pranab Sen

In recent years the framework of learning from label proportions (LLP) has been gaining importance in machine learning. In this setting, the training examples are aggregated into subsets or bags and only the average label per bag is…

Computational Complexity · Computer Science 2024-03-29 Venkatesan Guruswami , Rishi Saket