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We associate to each Boolean function a polynomial whose evaluations represents the distances from all possible Boolean affine functions. Both determining the coefficients of this polynomial from the truth table of the Boolean function and…

Information Theory · Computer Science 2014-04-11 Emanuele Bellini

It is known that there are classes of 2-CNFs requiring exponential size non-deterministic read-once branching programs to compute them. However, to the best of our knowledge, there are no superpolynomial lower bounds for branching programs…

Computational Complexity · Computer Science 2016-05-17 Igor Razgon

We introduce and investigate binary $(k,k)$-designs -- combinatorial structures which are related to binary orthogonal arrays. We derive general linear programming bound and propose as a consequence a universal bound on the minimum possible…

Combinatorics · Mathematics 2020-04-09 Todorka Alexandrova , Peter Boyvalenkov , Angel Dimitrov

Quantum query complexity plays an important role in studying quantum algorithms, which captures the most known quantum algorithms, such as search and period finding. A query algorithm applies $U_tO_x\cdots U_1O_xU_0$ to some input state,…

Quantum Physics · Physics 2024-03-18 Zipeng Wu , Shi-Yao Hou , Chao Zhang , Lvzhou Li , Bei Zeng

We recently introduced the graph invariant twin-width, and showed that first-order model checking can be solved in time $f(d,k)n$ for $n$-vertex graphs given with a witness that the twin-width is at most $d$, called $d$-contraction sequence…

Data Structures and Algorithms · Computer Science 2021-02-15 Édouard Bonnet , Colin Geniet , Eun Jung Kim , Stéphan Thomassé , Rémi Watrigant

The $k$-dimensional coding schemes refer to a collection of methods that attempt to represent data using a set of representative $k$-dimensional vectors, and include non-negative matrix factorization, dictionary learning, sparse coding,…

Machine Learning · Statistics 2016-04-26 Tongliang Liu , Dacheng Tao , Dong Xu

Neural Ordinary Differential Equations (N-ODEs) are a powerful building block for learning systems, which extend residual networks to a continuous-time dynamical system. We propose a Bayesian version of N-ODEs that enables well-calibrated…

Machine Learning · Computer Science 2020-02-19 Andreas Look , Melih Kandemir

Arunachalam and de Wolf (2018) showed that the sample complexity of quantum batch learning of boolean functions, in the realizable and agnostic settings, has the same form and order as the corresponding classical sample complexities. In…

Machine Learning · Computer Science 2025-07-30 Preetham Mohan , Ambuj Tewari

We present hierarchical learning, a novel variational architecture for efficient training of large-scale variational quantum circuits. We test and benchmark our technique for distribution loading with quantum circuit born machines (QCBMs).…

Quantum Physics · Physics 2023-11-23 Hrant Gharibyan , Vincent Su , Hayk Tepanyan

This paper presents a new compressed representation of Boolean functions, called CFLOBDDs (for Context-Free-Language Ordered Binary Decision Diagrams). They are essentially a plug-compatible alternative to BDDs (Binary Decision Diagrams),…

Symbolic Computation · Computer Science 2024-08-30 Meghana Sistla , Swarat Chaudhuri , Thomas Reps

The distributed operating room (OR) scheduling problem aims to find an assignment of surgeries to ORs across collaborating hospitals that share their waiting lists and ORs. We propose a stochastic extension of this problem where surgery…

Optimization and Control · Mathematics 2020-10-06 Cheng Guo , Merve Bodur , Dionne M. Aleman , David R. Urbach

We classify the Boolean degree $1$ functions of $k$-spaces in a vector space of dimension $n$ (also known as Cameron-Liebler classes) over the field with $q$ elements for $n \geq n_0(k, q)$. This also implies that two-intersecting sets with…

Combinatorics · Mathematics 2024-05-28 Ferdinand Ihringer

The topic of nonparametric estimation of smooth boundaries is extensively studied in the conventional setting where pairs of single covariate and response variable are observed. However, this traditional setting often suffers from the cost…

Statistics Theory · Mathematics 2026-04-07 Hiroki Waida , Takafumi Kanamori

Classification of datasets into two or more distinct classes is an important machine learning task. Many methods are able to classify binary classification tasks with a very high accuracy on test data, but cannot provide any easily…

Machine Learning · Computer Science 2020-08-26 Yashesh Dhebar , Sparsh Gupta , Kalyanmoy Deb

We study the deterministic query complexity of Boolean functions on slices of the hypercube. The $k^{th}$ slice $\binom{[n]}{k}$ of the hypercube $\{0,1\}^n$ is the set of all $n$-bit strings with Hamming weight $k$. We show that there…

Computational Complexity · Computer Science 2022-11-30 Farzan Byramji

Due to the rapid development of quantum computing, the compact representation of quantum operations based on decision diagrams has been received more and more attraction. Since variable orders have a significant impact on the size of the…

Quantum Physics · Physics 2022-07-26 Yonghong Li , Hao Miao

This paper presents a new data structure, called \emph{Weighted Context-Free-Language Ordered BDDs} (WCFLOBDDs), which are a hierarchically structured decision diagram, akin to Weighted BDDs (WBDDs) enhanced with a procedure-call mechanism.…

Formal Languages and Automata Theory · Computer Science 2024-08-30 Meghana Sistla , Swarat Chaudhuri , Thomas Reps

We propose a mathematical framework that we call quantum, higher-order Fourier analysis. This generalizes the classical theory of higher-order Fourier analysis, which led to many advances in number theory and combinatorics. We define a…

Quantum Physics · Physics 2025-09-09 Kaifeng Bu , Weichen Gu , Arthur Jaffe

The Sentential Decision Diagram (SDD) is a tractable representation of Boolean functions that subsumes the famous Ordered Binary Decision Diagram (OBDD) as a strict subset. SDDs are attracting much attention because they are more succinct…

Data Structures and Algorithms · Computer Science 2020-04-07 Kengo Nakamura , Shuhei Denzumi , Masaaki Nishino

It is classical that univariate algebraic functions satisfy linear differential equations with polynomial coefficients. Linear recurrences follow for the coefficients of their power series expansions. We show that the linear differential…

Symbolic Computation · Computer Science 2008-04-03 Alin Bostan , Frédéric Chyzak , Bruno Salvy , Grégoire Lecerf , Éric Schost