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Shannon entropy is widely used to measure the complexity of DNA sequences but suffers from saturation effects that limit its discriminative power for long uniform segments. We introduce a novel metric, the entropy rank ratio R, which…

Information Theory · Computer Science 2025-11-10 Emmanuel Pio Pastore , Giuseppe Passarino , Peppino Sapia , Francesco De Rango

We study a randomized quadrature algorithm to approximate the integral of periodic functions defined over the high-dimensional unit cube. Recent work by Kritzer, Kuo, Nuyens and Ullrich (2019) shows that rank-1 lattice rules with a randomly…

Numerical Analysis · Mathematics 2023-04-28 Josef Dick , Takashi Goda , Kosuke Suzuki

We establish new hardness results for decision tree optimization problems, adding to a line of work that dates back to Hyafil and Rivest in 1976. We prove, under randomized ETH, superpolynomial lower bounds for two basic problems: given an…

Computational Complexity · Computer Science 2022-10-13 Caleb Koch , Carmen Strassle , Li-Yang Tan

A seminal result of Nisan and Szegedy (STOC, 1992) shows that for any total Boolean function, the degree of the real polynomial that computes the function, and the minimal degree of a real polynomial that point-wise approximates the…

Computational Complexity · Computer Science 2025-07-21 Arkadev Chattopadhyay , Yogesh Dahiya , Shachar Lovett

We present an efficient parallel derandomization method for randomized algorithms that rely on concentrations such as the Chernoff bound. This settles a classic problem in parallel derandomization, which dates back to the 1980s. Consider…

Data Structures and Algorithms · Computer Science 2023-11-27 Mohsen Ghaffari , Christoph Grunau

Let $G=(V,E)$ be a simple graph with $|V|=n$ nodes and $|E|=m$ links, a subset $K \subseteq V$ of \emph{terminals}, a vector $p=(p_1,...,p_m) \in [0,1]^m$ and a positive integer $d$, called \emph{diameter}. We assume nodes are perfect but…

Data Structures and Algorithms · Computer Science 2014-10-02 Eduardo Canale , Pablo Romero , Gerardo Rubino

The bandwidth of a $n$-vertex graph $G$ is the smallest integer $b$ such that there exists a bijective function $f : V(G) \rightarrow \{1,...,n\}$, called a layout of $G$, such that for every edge $uv \in E(G)$, $|f(u) - f(v)| \leq b$. In…

Data Structures and Algorithms · Computer Science 2014-05-01 Markus Sortland Dregi , Daniel Lokshtanov

We study the largest component of a random (multi)graph on n vertices with a given degree sequence. We let n tend to infinity. Then, under some regularity conditions on the degree sequences, we give conditions on the asymptotic shape of the…

Combinatorics · Mathematics 2007-07-13 Svante Janson , Malwina Luczak

Decision tree learning has long been a central topic in theoretical computer science, driven by its practical importance. A fundamental and widely used method for decision tree construction is the top-down greedy heuristic, which…

Machine Learning · Computer Science 2026-05-14 Arshia Soltani Moakahr , Faraz Ghahremani , Kiarash Banihashem , MohammadTaghi Hajiaghayi

Fixed-order perturbative calculations for differential cross sections can suffer from non-physical artifacts: they can be non-positive, non-normalizable, and non-finite, none of which occur in experimental measurements. We propose a…

High Energy Physics - Phenomenology · Physics 2025-12-19 Rikab Gambhir , Radha Mastandrea

We propose a nonparametric estimator of the empirical distribution function (EDF) of the latent spot variance of the log-price of a financial asset. We show that over a fixed time span our realized EDF (or REDF) -- inferred from noisy…

Econometrics · Economics 2026-01-29 Kim Christensen , Martin Thyrsgaard , Bezirgen Veliyev

The results showing a quantum query complexity of $\Theta(N^{1/3})$ for the collision problem do not apply to random functions. The issues are two-fold. First, the $\Omega(N^{1/3})$ lower bound only applies when the range is no larger than…

Computational Complexity · Computer Science 2013-12-12 Mark Zhandry

Decomposable models and Bayesian networks can be defined as sequences of oligo-dimensional probability measures connected with operators of composition. The preliminary results suggest that the probabilistic models allowing for effective…

Artificial Intelligence · Computer Science 2013-02-08 Radim Jirousek

A fundamental question in computer science is: Is it harder to solve $n$ instances independently than to solve them simultaneously? This question, known as the direct sum question or direct sum theorem, has been paid much attention in…

Computational Complexity · Computer Science 2025-01-16 Daiki Suruga

A $(\beta,\delta,\Delta)$-padded decomposition of an edge-weighted graph $G = (V,E,w)$ is a stochastic decomposition into clusters of diameter at most $\Delta$ such that for every vertex $v\in V$, the probability that…

Data Structures and Algorithms · Computer Science 2025-10-15 Arnold Filtser , Tobias Friedrich , Davis Issac , Nikhil Kumar , Hung Le , Nadym Mallek , Ziena Zeif

We show a Birthday Paradox for self-intersections of Markov chains with uniform stationary distribution. As an application, we analyze Pollard's Rho algorithm for finding the discrete logarithm in a cyclic group $G$ and find that if the…

Probability · Mathematics 2016-09-08 Jeong Han Kim , Ravi Montenegro , Yuval Peres , Prasad Tetali

We study the relative complexity of equivalence relations and preorders from computability theory and complexity theory. Given binary relations $R, S$, a componentwise reducibility is defined by $ R\le S \iff \ex f \, \forall x, y \, [xRy…

Logic · Mathematics 2018-02-12 Egor Ianovski , Keng Meng Ng , Russell Miller , Andre Nies

We study algorithmic randomness and monotone complexity on product of the set of infinite binary sequences. We explore the following problems: monotone complexity on product space, Lambalgen's theorem for correlated probability,…

Information Theory · Computer Science 2010-06-29 Hayato Takahashi

We study zeroth-order optimization where solutions must minimize a cost $d(s)$ while maintaining high probability under a complex generative prior $L(s)$ (e.g., a parameterized model). This reduces to sampling from a target distribution…

Machine Learning · Computer Science 2026-05-06 Pranjal Awasthi , Sreenivas Gollapudi , Ravi Kumar , Kamesh Munagala

Over a finite field $\F_q$ the $(n,d,q)$-Reed-Muller code is the code given by evaluations of $n$-variate polynomials of total degree at most $d$ on all points (of $\F_q^n$). The task of testing if a function $f:\F_q^n \to \F_q$ is close to…

Information Theory · Computer Science 2015-03-20 Noga Ron-Zewi , Madhu Sudan