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Considering the optimal alignment of two i.i.d. random sequences of length $n$, we show that when the scoring function is chosen randomly, almost surely the empirical distribution of aligned letter pairs in all optimal alignments converges…

Probability · Mathematics 2012-11-26 Raphael Hauser , Heinrich Matzinger

We study the family of intersection graphs of low density objects in low dimensional Euclidean space. This family is quite general, and includes planar graphs. We prove that such graphs have small separators. Next, we present efficient…

Computational Geometry · Computer Science 2016-06-01 Sariel Har-Peled , Kent Quanrud

Large sets of combinatorial designs has always been a fascinating topic in design theory. These designs form a partition of the whole space into combinatorial designs with the same parameters. In particular, a large set of block designs,…

Combinatorics · Mathematics 2020-07-21 Tuvi Etzion , Junling Zhou

The problem of column subset selection asks for a subset of columns from an input matrix such that the matrix can be reconstructed as accurately as possible within the span of the selected columns. A natural extension is to consider a…

Machine Learning · Computer Science 2024-08-13 Antonis Matakos , Bruno Ordozgoiti , Suhas Thejaswi

Recent work proposes a family of contextual embeddings that significantly improves the accuracy of sequence labelers over non-contextual embeddings. However, there is no definite conclusion on whether we can build better sequence labelers…

Computation and Language · Computer Science 2021-06-03 Xinyu Wang , Yong Jiang , Nguyen Bach , Tao Wang , Zhongqiang Huang , Fei Huang , Kewei Tu

We derive a new estimate of the size of finite sets of points in metric spaces with few distances. The following applications are considered: (1) we improve the Ray-Chaudhuri--Wilson bound of the size of uniform intersecting families of…

Combinatorics · Mathematics 2011-04-29 Alexander Barg , Oleg R. Musin

We introduce the concepts of complex Grassmannian codes and designs. Let G(m,n) denote the set of m-dimensional subspaces of C^n: then a code is a finite subset of G(m,n) in which few distances occur, while a design is a finite subset of…

Combinatorics · Mathematics 2008-06-16 Aidan Roy

Subsampling is commonly used to overcome computational and economical bottlenecks in the analysis of finite populations and massive datasets. Existing methods are often limited in scope and use optimality criteria (e.g., A-optimality) with…

Statistics Theory · Mathematics 2023-04-07 Henrik Imberg , Marina Axelson-Fisk , Johan Jonasson

We study the complexity of the problem of searching for a set of patterns that separate two given sets of strings. This problem has applications in a wide variety of areas, most notably in data mining, computational biology, and in…

Computational Complexity · Computer Science 2016-12-20 Giuseppe Lancia , Luke Mathieson , Pablo Moscato

One of the main problems in random network coding is to compute good lower and upper bounds on the achievable cardinality of the so-called subspace codes in the projective space $\mathcal{P}_q(n)$ for a given minimum distance. The…

Information Theory · Computer Science 2020-11-16 Tao Feng , Sascha Kurz , Shuangqing Liu

We consider a problem of maximizing the product of the sizes of two uniform cross-$t$-intersecting families of sets. We show that the value of this maximum is at most polynomially larger (in the size of a ground set) than a quantity…

Combinatorics · Mathematics 2021-02-23 Georgii P. Bulgakov , Alexander Kozachinskiy , Mikhail N. Vyalyi

In recent years, the interest in interpretable classification models has grown. One of the proposed ways to improve the interpretability of a rule-based classification model is to use sets (unordered collections) of rules, instead of lists…

Machine Learning · Computer Science 2020-03-31 Thiago Zafalon Miranda , Diorge Brognara Sardinha , Ricardo Cerri

Combinatorial discrepancy is a complexity measure of a collection of sets which quantifies how well the sets in the collection can be simultaneously balanced. More precisely, we are given an n-point set $P$, and a collection $\mathcal{F} =…

Combinatorics · Mathematics 2017-04-18 Aleksandar Nikolov

We address the problem of constructing a fast lossless code in the case when the source alphabet is large. The main idea of the new scheme may be described as follows. We group letters with small probabilities in subsets (acting as super…

Information Theory · Computer Science 2007-07-13 Boris Ryabko , Jaakko Astola , Karen Egiazarian

Separating codes have their applications in collusion-secure fingerprinting for generic digital data, while they are also related to the other structures including hash family, intersection code and group testing. In this paper we study…

Information Theory · Computer Science 2013-11-25 Ryul Kim , Myong-Son Sin , Ok-Hyon Song

An important first step in computational SAR modeling is to transform the compounds into a representation that can be processed by predictive modeling techniques. This is typically a feature vector where each feature indicates the presence…

Computational Engineering, Finance, and Science · Computer Science 2015-01-14 Albrecht Zimmermann , Björn Bringmann , Luc De Raedt

In the SetDisjointness problem, a collection of $m$ sets $S_1,S_2,...,S_m$ from some universe $U$ is preprocessed in order to answer queries on the emptiness of the intersection of some two query sets from the collection. In the…

Data Structures and Algorithms · Computer Science 2019-10-03 Isaac Goldstein , Moshe Lewenstein , Ely Porat

A family X of sets is said to be intersecting if any two members of X have non-empty intersection. It is a well-known and simple fact that an intersecting family of subsets of [n]={1,2,...,n} can contain at most 2^(n-1) sets. Katona, Katona…

Combinatorics · Mathematics 2011-08-17 Paul A. Russell

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu

Deep neural network-based architectures give promising results in various domains including pattern recognition. Finding the optimal combination of the hyper-parameters of such a large-sized architecture is tedious and requires a large…

Computer Vision and Pattern Recognition · Computer Science 2020-03-17 Animesh Singh , Sandip Saha , Ritesh Sarkhel , Mahantapas Kundu , Mita Nasipuri , Nibaran Das