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In the paper, we consider several types of queries for classical and new problems of learning and testing read-once functions. In several cases, the border between polynomial and exponential complexities is obtained.

Computational Complexity · Computer Science 2009-12-21 Andrey A. Voronenko

Consider the following decision problem: for a given monotone Boolean function $f$ decide, whether $f$ is read-once. For this problem, it is essential how the input function $f$ is represented. Our contribution consists of the following two…

Computational Complexity · Computer Science 2018-07-10 Alexander Kozachinskiy

We consider the problem of proper learning a Boolean Halfspace with integer weights $\{0,1,\ldots,t\}$ from membership queries only. The best known algorithm for this problem is an adaptive algorithm that asks $n^{O(t^5)}$ membership…

Machine Learning · Computer Science 2014-05-08 Hasan Abasi , Ali Z. Abdi , Nader H. Bshouty

In this paper we study the complexity of quantum query algorithms computing the value of Boolean function and its relation to the degree of algebraic polynomial representing this function. We pay special attention to Boolean functions with…

Quantum Physics · Physics 2012-03-24 Alina Dubrovska Vasilieva , Taisija Mischenko-Slatenkova

The goal of the paper is to relate complexity measures associated with the evaluation of Boolean functions (certificate complexity, decision tree complexity) and learning dimensions used to characterize exact learning (teaching dimension,…

Machine Learning · Computer Science 2012-05-22 Sergiu Goschin

The approximate degree of a Boolean function is the minimum degree of real polynomial that approximates it pointwise. For any Boolean function, its approximate degree serves as a lower bound on its quantum query complexity, and generically…

Computational Complexity · Computer Science 2023-05-23 Mark Bun , Nadezhda Voronova

We consider the complexity of equivalence and learning for multiplicity tree automata, i.e., weighted tree automata over a field. We first show that the equivalence problem is logspace equivalent to polynomial identity testing, the…

Machine Learning · Computer Science 2014-12-01 Ines Marusic , James Worrell

It has been a long-standing goal in machine learning, as well as in AI more generally, to develop life-long learning systems that learn many different tasks over time, and reuse insights from tasks learned, "learning to learn" as they do…

Machine Learning · Computer Science 2014-12-08 Maria-Florina Balcan , Avrim Blum , Santosh Vempala

We introduce the problem of learning mixtures of $k$ subcubes over $\{0,1\}^n$, which contains many classic learning theory problems as a special case (and is itself a special case of others). We give a surprising $n^{O(\log k)}$-time…

Machine Learning · Computer Science 2019-02-20 Sitan Chen , Ankur Moitra

The purpose of this paper is to provide efficient algorithms that decide membership for classes of several Boolean hierarchies for which efficiency (or even decidability) were previously not known. We develop new forbidden-chain…

Computational Complexity · Computer Science 2008-02-21 Christian Glasser , Heinz Schmitz , Victor Selivanov

Active learning is a subfield of machine learning, in which the learning algorithm is allowed to choose the data from which it learns. In some cases, it has been shown that active learning can yield an exponential gain in the number of…

Machine Learning · Computer Science 2020-12-22 Ori Kelner

In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum…

Quantum Physics · Physics 2007-05-23 Alp Atici , Rocco A. Servedio

The approximate degree of a Boolean function $f(x_{1},x_{2},\ldots,x_{n})$ is the minimum degree of a real polynomial that approximates $f$ pointwise within $1/3$. Upper bounds on approximate degree have a variety of applications in…

Computational Complexity · Computer Science 2018-01-16 Alexander A. Sherstov

We establish a lower bound of $\Omega{(\sqrt{n})}$ on the bounded-error quantum query complexity of read-once Boolean functions, providing evidence for the conjecture that $\Omega(\sqrt{D(f)})$ is a lower bound for all Boolean functions.…

Quantum Physics · Physics 2007-05-23 Howard Barnum , Michael Saks

We study the problem of learning a finite union of integer (axis-aligned) hypercubes over the d-dimensional integer lattice, i.e., whose edges are parallel to the coordinate axes. This is a natural generalization of the classic problem in…

Machine Learning · Computer Science 2021-05-28 Oliver Markgraf , Daniel Stan , Anthony W. Lin

We study the uniform query reliability problem, which asks, for a fixed Boolean query Q, given an instance I, how many subinstances of I satisfy Q. Equivalently, this is a restricted case of Boolean query evaluation on tuple-independent…

Databases · Computer Science 2023-01-18 Antoine Amarilli

We investigate the randomized decision tree complexity of a specific class of read-once threshold functions. A read-once threshold formula can be defined by a rooted tree, every internal node of which is labeled by a threshold function…

Computational Complexity · Computer Science 2023-10-19 Nikos Leonardos

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…

To help a user specify and verify quantified queries --- a class of database queries known to be very challenging for all but the most expert users --- one can question the user on whether certain data objects are answers or non-answers to…

We introduce a new model of membership query (MQ) learning, where the learning algorithm is restricted to query points that are \emph{close} to random examples drawn from the underlying distribution. The learning model is intermediate…

Machine Learning · Computer Science 2013-04-19 Pranjal Awasthi , Vitaly Feldman , Varun Kanade
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