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We study the problem of computing the maximum likelihood estimator (MLE) of multivariate log-concave densities. Our main result is the first computationally efficient algorithm for this problem. In more detail, we give an algorithm that, on…

Data Structures and Algorithms · Computer Science 2018-12-14 Ilias Diakonikolas , Anastasios Sidiropoulos , Alistair Stewart

We give deterministic distributed $(1+\epsilon)$-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in $O(\frac{1}{\epsilon} \log n)$ rounds,…

Data Structures and Algorithms · Computer Science 2018-05-15 Christian Konrad , Viktor Zamaraev

We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML…

Machine Learning · Computer Science 2017-12-21 Dmitri S. Pavlichin , Jiantao Jiao , Tsachy Weissman

This paper considers the multi-parametric linear complementarity problem (pLCP) with sufficient matrices. The main result is an algorithm to find a polyhedral decomposition of the set of feasible parameters and to construct a piecewise…

Optimization and Control · Mathematics 2008-07-16 Sebastiano Columbano , Komei Fukuda , Colin Jones

Policy optimization methods with function approximation are widely used in multi-agent reinforcement learning. However, it remains elusive how to design such algorithms with statistical guarantees. Leveraging a multi-agent performance…

Machine Learning · Computer Science 2023-05-09 Yulai Zhao , Zhuoran Yang , Zhaoran Wang , Jason D. Lee

We investigate the existence of approximation algorithms for maximization of submodular functions, that run in fixed parameter tractable (FPT) time. Given a non-decreasing submodular set function $v: 2^X \to \mathbb{R}$ the goal is to…

Data Structures and Algorithms · Computer Science 2021-04-21 Piotr Skowron

We present a simple distributed $\Delta$-approximation algorithm for maximum weight independent set (MaxIS) in the $\mathsf{CONGEST}$ model which completes in $O(\texttt{MIS}(G)\cdot \log W)$ rounds, where $\Delta$ is the maximum degree,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-02 Reuven Bar-Yehuda , Keren Censor-Hillel , Mohsen Ghaffari , Gregory Schwartzman

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

In this contribution, we are concerned with parameter optimization problems that are constrained by multiscale PDE state equations. As an efficient numerical solution approach for such problems, we introduce and analyze a new relaxed and…

Numerical Analysis · Mathematics 2023-04-13 Tim Keil , Mario Ohlberger

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

We consider the class of disjoint bilinear programs $ \max \, \{ \mathbf{x}^T\mathbf{y} \mid \mathbf{x} \in \mathcal{X}, \;\mathbf{y} \in \mathcal{Y}\}$ where $\mathcal{X}$ and $\mathcal{Y}$ are packing polytopes. We present an…

Optimization and Control · Mathematics 2023-06-02 Omar El Housni , Ayoub Foussoul , Vineet Goyal

We study the Maximum Independent Set (MIS) problem on general graphs within the framework of learning-augmented algorithms. The MIS problem is known to be NP-hard and is also NP-hard to approximate to within a factor of $n^{1-\delta}$ for…

Data Structures and Algorithms · Computer Science 2024-07-17 Vladimir Braverman , Prathamesh Dharangutte , Vihan Shah , Chen Wang

A numerical method is developed to solve linear semi-infinite programming problem (LSIP) in which the iterates produced by the algorithm are feasible for the original problem. This is achieved by constructing a sequence of standard linear…

Optimization and Control · Mathematics 2021-01-26 Shuxiong Wang

A dynamic graph algorithm is a data structure that supports edge insertions, deletions, and specific problem queries. While extensive research exists on dynamic algorithms for graph problems solvable in polynomial time, most of these…

Data Structures and Algorithms · Computer Science 2024-07-10 Jannick Borowitz , Ernestine Großmann , Christian Schulz

We extend classical methods of computational complexity to the realm of distributed computing, where they sometimes prove more effective than in their original context. Our focus is on decision problems in the LOCAL model, a setting in…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-08 Fabian Reiter

We develop a randomized approximation algorithm for the classical maximum coverage problem, which given a list of sets $A_1,A_2,\cdots, A_m$ and integer parameter $k$, select $k$ sets $A_{i_1}, A_{i_2},\cdots, A_{i_k}$ for maximum union…

Data Structures and Algorithms · Computer Science 2016-07-21 Bin Fu

We present improved results for approximating maximum-weight independent set ($\MaxIS$) in the CONGEST and LOCAL models of distributed computing. Given an input graph, let $n$ and $\Delta$ be the number of nodes and maximum degree,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-20 Ken-ichi Kawarabayashi , Seri Khoury , Aaron Schild , Gregory Schwartzman

Maximum independent set from a given set $D$ of unit disks intersecting a horizontal line can be solved in $O(n^2)$ time and $O(n^2)$ space. As a corollary, we design a factor 2 approximation algorithm for the maximum independent set…

Computational Geometry · Computer Science 2016-11-11 Subhas C. Nandy , Supantha Pandit , Sasanka Roy

We study geometric variations of the discriminating code problem. In the \emph{discrete version} of the problem, a finite set of points $P$ and a finite set of objects $S$ are given in $\mathbb{R}^d$. The objective is to choose a subset…

Computational Geometry · Computer Science 2023-06-30 Sanjana Dey , Florent Foucaud , Subhas C Nandy , Arunabha Sen

Sparse structure learning in high-dimensional Gaussian graphical models is an important problem in multivariate statistical signal processing; since the sparsity pattern naturally encodes the conditional independence relationship among…

Methodology · Statistics 2023-09-26 Ksheera Sagar , Jyotishka Datta , Sayantan Banerjee , Anindya Bhadra