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Boolean matrix factorization (BMF) is a popular and powerful technique for inferring knowledge from data. The mining result is the Boolean product of two matrices, approximating the input dataset. The Boolean product is a disjunction of…

Machine Learning · Computer Science 2019-07-02 Sibylle Hess , Nico Piatkowski , Katharina Morik

Lifting theorems are theorems that bound the communication complexity of a composed function $f\circ g^{n}$ in terms of the query complexity of $f$ and the communication complexity of $g$. Such theorems constitute a powerful generalization…

Computational Complexity · Computer Science 2024-04-12 Yahel Manor , Or Meir

The sum-product algorithm for decoding of binary codes is analyzed for bipartite graphs in which the check nodes all have degree $2$. The algorithm simplifies dramatically and may be expressed using linear algebra. Exact results about the…

Information Theory · Computer Science 2014-11-11 John O. Brevik , Michael E. O'Sullivan

This work considers a generalization of Grover's search problem, viz., to find any one element in a set of acceptable choices which constitute a fraction f of the total number of choices in an unsorted data base. An infinite family of…

Quantum Physics · Physics 2009-11-07 Chia-Ren Hu

In general, while obtaining the probability density function of sums and products of shifted random variables, ordinary analytical methods such as Fourier and Mellin transforms tend to provide integrals which cannot be expressed in terms of…

Complex Variables · Mathematics 2013-02-14 Pushpa N. rathie , Arjun K. Rathie , Luan C. de S. M. Ozelim

Density deconvolution deals with the estimation of the probability density function $f$ of a random signal from $n\geq1$ data observed with independent and known additive random noise. This is a classical problem in statistics, for which…

Methodology · Statistics 2024-12-16 Stefano Favaro , Sandra Fortini

That the logarithmic distribution manifests itself in the random as well as in the deterministic (multiplication processes) has long intrigued researchers in Benford's Law. In this article it is argued that it springs from one common…

Statistics Theory · Mathematics 2012-11-01 Alex Ely Kossovsky

Consider the model where we can access a parity function through random uniform labeled examples in the presence of random classification noise. In this paper, we show that approximating the number of relevant variables in the parity…

Machine Learning · Computer Science 2024-07-17 Nader H. Bshouty , George Haddad

Product formulas can be used to simulate Hamiltonian dynamics on a quantum computer by approximating the exponential of a sum of operators by a product of exponentials of the individual summands. This approach is both straightforward and…

Quantum Physics · Physics 2019-09-04 Andrew M. Childs , Aaron Ostrander , Yuan Su

We employ techniques from group theory to show that, in many cases, counting problems on graphs are almost as hard to solve in a small number of instances as they are in all instances. Specifically, we show the following results. 1.…

Computational Complexity · Computer Science 2024-11-15 Tejas Nareddy , Abhishek Mishra

The main reason for query model's prominence in complexity theory and quantum computing is the presence of concrete lower bounding techniques: polynomial and adversary method. There have been considerable efforts to give lower bounds using…

Quantum Physics · Physics 2024-02-20 Rajat Mittal , Sanjay S Nair , Sunayana Patro

We show that for a relation $f\subseteq \{0,1\}^n\times \mathcal{O}$ and a function $g:\{0,1\}^{m}\times \{0,1\}^{m} \rightarrow \{0,1\}$ (with $m= O(\log n)$), $$\mathrm{R}_{1/3}(f\circ g^n) = \Omega\left(\mathrm{R}_{1/3}(f) \cdot…

Computational Complexity · Computer Science 2018-01-23 Anurag Anshu , Naresh B. Goud , Rahul Jain , Srijita Kundu , Priyanka Mukhopadhyay

We provide faster algorithms for the problem of Gaussian summation, which occurs in many machine learning methods. We develop two new extensions - an O(Dp) Taylor expansion for the Gaussian kernel with rigorous error bounds and a new error…

Machine Learning · Computer Science 2012-07-02 Dongryeol Lee , Alexander G. Gray

This paper gives a dichotomy theorem for the complexity of computing the partition function of an instance of a weighted Boolean constraint satisfaction problem. The problem is parameterised by a finite set F of non-negative functions that…

Computational Complexity · Computer Science 2009-02-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

Polynomial multiplication is known to have quasi-linear complexity in both the dense and the sparse cases. Yet no truly linear algorithm has been given in any case for the problem, and it is not clear whether it is even possible. This…

Symbolic Computation · Computer Science 2021-01-07 Pascal Giorgi , Bruno Grenet , Armelle Perret du Cray

Nisan and Szegedy (CC 1994) showed that any Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ that depends on all its input variables, when represented as a real-valued multivariate polynomial $P(x_1,\ldots,x_n)$, has degree at least $\log…

Computational Complexity · Computer Science 2021-07-08 Srikanth Srinivasan , S. Venkitesh

In this paper, we will describe a new factorization algorithm based on the continuous representation of Gauss sums, generalizable to orders j>2. Such an algorithm allows one, for the first time, to find all the factors of a number N in a…

Quantum Physics · Physics 2015-06-10 Vincenzo Tamma , Heyi Zhang , Xuehua He , Augusto Garuccio , Yanhua Shih

This paper studies the hazard-free formula complexity of Boolean functions. Our first result shows that unate functions are the only Boolean functions for which the monotone formula complexity of the hazard-derivative equals the hazard-free…

Computational Complexity · Computer Science 2025-06-17 Leah London Arazi , Amir Shpilka

In this article, we consider the general problem of checking the correctness of matrix multiplication. Given three $n \times n$ matrices $A$, $B$, and $C$, the goal is to verify that $A \times B=C$ without carrying out the computationally…

Data Structures and Algorithms · Computer Science 2017-05-31 Hao Ji , Michael Mascagni , Yaohang Li

We show an essentially tight bound on the number of adaptively chosen statistical queries that a computationally efficient algorithm can answer accurately given $n$ samples from an unknown distribution. A statistical query asks for the…

Cryptography and Security · Computer Science 2015-02-23 Thomas Steinke , Jonathan Ullman