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We prove that in every metric space where no line contains all the points, there are at least $\Omega(n^{2/3})$ lines. This improves the previous $\Omega(\sqrt{n})$ lower bound on the number of lines in general metric space, and also…

Combinatorics · Mathematics 2024-12-10 Congkai Huang

This paper discovers that the neural network with lower decision boundary (DB) variability has better generalizability. Two new notions, algorithm DB variability and $(\epsilon, \eta)$-data DB variability, are proposed to measure the…

Machine Learning · Computer Science 2023-12-27 Shiye Lei , Fengxiang He , Yancheng Yuan , Dacheng Tao

We describe a data structure that supports access, rank and select queries, as well as symbol insertions and deletions, on a string $S[1,n]$ over alphabet $[1..\sigma]$ in time $O(\lg n/\lg\lg n)$, which is optimal even on binary sequences…

Data Structures and Algorithms · Computer Science 2013-02-04 Gonzalo Navarro , Yakov Nekrich

Bilevel optimization problems, which are problems where two optimization problems are nested, have more and more applications in machine learning. In many practical cases, the upper and the lower objectives correspond to empirical risk…

Machine Learning · Statistics 2024-12-03 Mathieu Dagréou , Thomas Moreau , Samuel Vaiter , Pierre Ablin

Recently, Ezra and Sharir [ES22a] showed an $O(n^{3/2+\sigma})$ space and $O(n^{1/2+\sigma})$ query time data structure for ray shooting among triangles in $\mathbb{R}^3$. This improves the upper bound given by the classical…

Computational Geometry · Computer Science 2023-02-23 Peyman Afshani , Pingan Cheng

The problem of learning threshold functions is a fundamental one in machine learning. Classical learning theory implies sample complexity of $O(\xi^{-1} \log(1/\beta))$ (for generalization error $\xi$ with confidence $1-\beta$). The private…

Machine Learning · Computer Science 2022-11-14 Edith Cohen , Xin Lyu , Jelani Nelson , Tamás Sarlós , Uri Stemmer

We provide a new upper bound for sampling numbers $(g_n)_{n\in \mathbb{N}}$ associated to the compact embedding of a separable reproducing kernel Hilbert space into the space of square integrable functions. There are universal constants…

Numerical Analysis · Mathematics 2021-02-11 Nicolas Nagel , Martin Schäfer , Tino Ullrich

For any $\epsilon \in (0,1)$, a $(1+\epsilon)$-approximate range mode query asks for the position of an element whose frequency in the query range is at most a factor $(1+\epsilon)$ smaller than the true mode. For this problem, we design an…

Data Structures and Algorithms · Computer Science 2019-07-22 Hicham El-Zein , Meng He , J. Ian Munro , Yakov Nekrich , Bryce Sandlund

In a landmark paper, P\v{a}tra\c{s}cu demonstrated how a single lower bound for the static data structure problem of reachability in the butterfly graph, could be used to derive a wealth of new and previous lower bounds via reductions.…

Data Structures and Algorithms · Computer Science 2020-11-03 Kasper Green Larsen , Jonathan Lindegaard Starup , Jesper Steensgaard

In this technical note, we present a new theoretical result for resource optimization with non-orthogonal multiple access (NOMA). For multi-cell scenarios, a so-called load-coupling model has been proposed to characterize the presence of…

Information Theory · Computer Science 2020-09-22 Lei You , Di Yuan

Pattern-avoiding permutations are a central object of study in both combinatorics and theoretical computer science. In this paper we design a data structure that can store any size-$n$ permutation $\tau$ that avoids an arbitrary (and…

Data Structures and Algorithms · Computer Science 2025-10-24 László Kozma , Michal Opler

We prove a lower bound on the eigenvalues $\lambda_k$, $k\in\mathbb{N}$, of the Dirichlet Laplacian of a bounded domain $\Omega\subset\mathbb{R}^n$ of volume $V$: $$ \lambda_k \geq C_n\bigg( \delta\frac{k}{V}\bigg)^{2/n} $$ where $\delta$…

Spectral Theory · Mathematics 2015-12-29 Neal Coleman

We consider the problem of estimating the support size of a distribution $D$. Our investigations are pursued through the lens of distribution testing and seek to understand the power of conditional sampling (denoted as COND), wherein one is…

Data Structures and Algorithms · Computer Science 2022-11-23 Diptarka Chakraborty , Gunjan Kumar , Kuldeep S. Meel

Shannon's entropy is a definitive lower bound for statistical compression. Unfortunately, no such clear measure exists for the compressibility of repetitive strings. Thus, ad hoc measures are employed to estimate the repetitiveness of…

Data Structures and Algorithms · Computer Science 2023-11-16 Giulia Bernardini , Gabriele Fici , Paweł Gawrychowski , Solon P. Pissis

Given an array of distinct integers $A[1\ldots n]$, the Range Minimum Query (RMQ) problem requires us to construct a data structure from $A$, supporting the RMQ query: given an interval $[a,b]\subseteq[1,n]$, return the index of the minimum…

Data Structures and Algorithms · Computer Science 2022-02-10 Mingmou Liu

We consider ensembles of Wigner matrices, whose entries are (up to the symmetry constraints) independent and identically distributed random variables. We show the convergence of the Stieltjes transform towards the Stieltjes transform of the…

Mathematical Physics · Physics 2014-12-05 Claudio Cacciapuoti , Anna Maltsev , Benjamin Schlein

Diestel and M\"uller showed that the connected tree-width of a graph $G$, i.e., the minimum width of any tree-decomposition with connected parts, can be bounded in terms of the tree-width of $G$ and the largest length of a geodesic cycle in…

Combinatorics · Mathematics 2017-02-15 Matthias Hamann , Daniel Weißauer

This work reports on two results. At first we revisit the Berg and Purcell calculation that provides a lower bound to the error in concentration measurement by cells, by considering the realistic case when the cell starts measuring the…

Subcellular Processes · Quantitative Biology 2022-04-06 Vaibhav Wasnik

In the adaptive bitprobe model answering membership queries in two bitprobes, we consider the class of restricted schemes as introduced by Kesh and Sharma (Discrete Applied Mathematics 2021). In that paper, the authors showed that such…

Data Structures and Algorithms · Computer Science 2022-04-11 Sreshth Aggarwal , Deepanjan Kesh , Divyam Singal

Sample-efficient machine learning (SEML) has been widely applied to find optimal latency and power tradeoffs for configurable computer systems. Instead of randomly sampling from the configuration space, SEML reduces the search cost by…

Machine Learning · Computer Science 2022-04-12 Yi Ding , Alex Renda , Ahsan Pervaiz , Michael Carbin , Henry Hoffmann