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Supercomputers are equipped with an increasingly large number of cores to use computational power as a way of solving problems that are otherwise intractable. Unfortunately, getting serial algorithms to run in parallel to take advantage of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-31 Faisal N. Abu-Khzam , Khuzaima Daudjee , Amer E. Mouawad , Naomi Nishimura

In optimization problems involving smooth functions and real and matrix variables, that contain matrix semidefiniteness constraints, consider the following change of variables: Replace the positive semidefinite matrix $X \in \mathbb{S}^d$,…

Optimization and Control · Mathematics 2025-02-05 Lijun Ding , Stephen J. Wright

Over the past few years, self-attention is shining in the field of deep learning, especially in the domain of natural language processing(NLP). Its impressive effectiveness, along with ubiquitous implementations, have aroused our interest…

Machine Learning · Computer Science 2020-12-03 Mingfei Yu , Masahiro Fujita

In information visualization, the position of symbols often encodes associated data values. When visualizing data elements with both a numerical and a categorical dimension, positioning in the categorical axis admits some flexibility. This…

Computational Geometry · Computer Science 2025-05-22 Bernd Gärtner , Vishwas Kalani , Meghana M. Reddy , Wouter Meulemans , Bettina Speckmann , Miloš Stojaković

This paper is about partitioning in parallel and distributed simulation. That means decomposing the simulation model into a numberof components and to properly allocate them on the execution units. An adaptive solution based on…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-07 Gabriele D'Angelo

Simultaneous localization and Planning (SLAP) is a crucial ability for an autonomous robot operating under uncertainty. In its most general form, SLAP induces a continuous POMDP (partially-observable Markov decision process), which needs to…

We propose an algorithm, called OEM (a.k.a. orthogonalizing EM), intended for var- ious least squares problems. The first step, named active orthogonization, orthogonalizes an arbi- trary regression matrix by elaborately adding more rows.…

Computation · Statistics 2013-08-16 Shifeng Xiong , Bin Dai , Peter Z. G. Qian

Classes of set functions along with a choice of ground set are a bedrock to determine and develop corresponding variants of greedy algorithms to obtain efficient solutions for combinatorial optimization problems. The class of approximate…

Optimization and Control · Mathematics 2021-08-20 Praneeth Vepakomma , Yulia Kempner , Ramesh Raskar

This paper is concerned with problems relevant to motion planning in robotics. Configuration spaces are of practical relevance in designing safe control schemes for robots moving on a track. The topological complexity of a configuration…

Algebraic Topology · Mathematics 2019-05-02 Allaoua Boughrira , Hellen Colman

Given a graph with positive and negative edge labels, the correlation clustering problem aims to cluster the nodes so to minimize the total number of between-cluster positive and within-cluster negative edges. This problem has many…

Data Structures and Algorithms · Computer Science 2024-06-17 Mina Dalirrooyfard , Konstantin Makarychev , Slobodan Mitrović

In this work, we present a constant-round algorithm for the $2$-ruling set problem in the Congested Clique model. As a direct consequence, we obtain a constant round algorithm in the MPC model with linear space-per-machine and optimal total…

Data Structures and Algorithms · Computer Science 2023-10-11 Mélanie Cambus , Fabian Kuhn , Shreyas Pai , Jara Uitto

We study the problem of scheduling a set of jobs with release dates, deadlines and processing requirements (or works), on parallel speed-scaled processors so as to minimize the total energy consumption. We consider that both preemption and…

Data Structures and Algorithms · Computer Science 2011-07-13 Eric Angel , Evripidis Bampis , Fadi Kacem , Dimitrios Letsios

In this paper, we propose a distributed algorithm for stochastic smooth, non-convex optimization. We assume a worker-server architecture where $N$ nodes, each having $n$ (potentially infinite) number of samples, collaborate with the help of…

Optimization and Control · Mathematics 2020-11-09 Pranay Sharma , Swatantra Kafle , Prashant Khanduri , Saikiran Bulusu , Ketan Rajawat , Pramod K. Varshney

We introduce and analyze a model for self-reconfigurable robots made up of unit-cube modules. Compared to past models, our model aims to newly capture two important practical aspects of real-world robots. First, modules often do not occupy…

This paper studies the problem of finding an $(1+\epsilon)$-approximate solution to positive semidefinite programs. These are semidefinite programs in which all matrices in the constraints and objective are positive semidefinite and all…

Data Structures and Algorithms · Computer Science 2016-02-23 Richard Peng , Kanat Tangwongsan , Peng Zhang

This paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programming (PQP) through dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data…

Systems and Control · Electrical Eng. & Systems 2019-11-26 Kooktae Lee

This paper explores general multi-robot task and motion planning, where multiple robots in close proximity manipulate objects while satisfying constraints and a given goal. In particular, we formulate the plan refinement problem--which,…

Robotics · Computer Science 2023-09-19 Yoonchang Sung , Rahul Shome , Peter Stone

This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical…

Optimization and Control · Mathematics 2013-09-06 Peng Guo , Wenming Cheng , Yi Wang

We give both efficient algorithms and hardness results for reconfiguring between two connected configurations of modules in the hexagonal grid. The reconfiguration moves that we consider are "pivots", where a hexagonal module rotates around…

In this paper we consider parallelization for applications whose objective can be expressed as maximizing a non-monotone submodular function under a cardinality constraint. Our main result is an algorithm whose approximation is arbitrarily…

Data Structures and Algorithms · Computer Science 2018-07-31 Eric Balkanski , Adam Breuer , Yaron Singer