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This paper focuses on the statistical analysis of shapes of data objects called shape graphs, a set of nodes connected by articulated curves with arbitrary shapes. A critical need here is a constrained registration of points (nodes to…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Shenyuan Liang , Mauricio Pamplona Segundo , Sathyanarayanan N. Aakur , Sudeep Sarkar , Anuj Srivastava

In recent years, several convergent multi-block variants of the alternating direction method of multipliers (ADMM) have been proposed for solving the convex quadratic semidefinite programming via its dual, which is naturally a 3-block…

Optimization and Control · Mathematics 2018-07-06 Xiaokai Chang , Liang Chen , Sanyang Liu

We revisit existing linear computation coding (LCC) algorithms, and introduce a new framework that measures the computational cost of computing multidimensional linear functions, not only in terms of the number of additions, but also with…

Information Theory · Computer Science 2024-01-17 Hans Rosenberger , Ali Bereyhi , Ralf R. Müller

We describe algorithms to efficiently compute minimum $(s,t)$-cuts and global minimum cuts of undirected surface-embedded graphs. Given an edge-weighted undirected graph $G$ with $n$ vertices embedded on an orientable surface of genus $g$,…

Data Structures and Algorithms · Computer Science 2019-10-11 Erin W. Chambers , Jeff Erickson , Kyle Fox , Amir Nayyeri

Stochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions…

Machine Learning · Statistics 2022-10-07 Saad Mohamad , Hamad Alamri , Abdelhamid Bouchachia

We present a new adaptive parallel algorithm for the challenging problem of multi-dimensional numerical integration on massively parallel architectures. Adaptive algorithms have demonstrated the best performance, but efficient many-core…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-24 Ioannis Sakiotis , Kamesh Arumugam , Marc Paterno , Desh Ranjan , Balša Terzić , Mohammad Zubair

Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and architecture weights alternatively in a differential manner.…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Benteng Ma , Jing Zhang , Yong Xia , Dacheng Tao

Software requirements selection aims to find an optimal subset of the requirements with the highest value while respecting the project constraints. But the value of a requirement may depend on the presence or absence of other requirements…

Software Engineering · Computer Science 2020-03-13 Davoud Mougouei , David M W Powers

In the era of big data, optimizing large scale machine learning problems becomes a challenging task and draws significant attention. Asynchronous optimization algorithms come out as a promising solution. Recently, decoupled asynchronous…

Machine Learning · Computer Science 2016-09-30 Zhouyuan Huo , Bin Gu , Heng Huang

Constraint Logic Programming (CLP) is a language scheme for combining two declarative paradigms: constraint solving and logic programming. Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact…

Logic in Computer Science · Computer Science 2018-12-03 Moreno Falaschi , Carlos Olarte

Anomaly detection in high-dimensional time series data is pivotal for numerous industrial applications. Recent advances in multivariate time series anomaly detection (TSAD) have increasingly leveraged graph structures to model…

Machine Learning · Computer Science 2025-09-23 Jiazhen Chen , Mingbin Feng , Tony S. Wirjanto

We describe a practical algorithm to compute the (oriented) genus of a graph, give results of the program implementing this algorithm, and compare the performance to existing algorithms. The aim of this algorithm is to be fast enough for…

Combinatorics · Mathematics 2020-05-19 G. Brinkmann

The implementation of a vast majority of machine learning (ML) algorithms boils down to solving a numerical optimization problem. In this context, Stochastic Gradient Descent (SGD) methods have long proven to provide good results, both in…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-10-06 Janis Keuper , Franz-Josef Pfreundt

There has been a growing interest in causal learning in recent years. Commonly used representations of causal structures, including Bayesian networks and structural equation models (SEM), take the form of directed acyclic graphs (DAGs). We…

Machine Learning · Computer Science 2025-11-20 Pavel Rytir , Ales Wodecki , Jakub Marecek

Several applications of slicing require a program to be sliced with respect to more than one slicing criterion. Program specialization, parallelization and cohesion measurement are examples of such applications. These applications can…

Programming Languages · Computer Science 2017-09-26 Prasanna Kumar K. , Amitabha Sanyal , Amey Karkare

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

We introduce a novel neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. This advanced slicer can work on models with diverse representations and intricate topology. The approach…

Computational Geometry · Computer Science 2024-05-28 Tao Liu , Tianyu Zhang , Yongxue Chen , Yuming Huang , Charlie C. L. Wang

Control parallelism and data parallelism is mostly reasoned and optimized as separate functions. Because of this, workloads that are irregular, fine-grain and dynamic such as dynamic graph processing become very hard to scale. An…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-08 Bibrak Qamar Chandio , Thomas Sterling , Prateek Srivastava

The 3D Gaussian Splatting (3DGS)-based SLAM system has garnered widespread attention due to its excellent performance in real-time high-fidelity rendering. However, in real-world environments with dynamic objects, existing 3DGS-based SLAM…

Robotics · Computer Science 2025-02-19 Mingrui Li , Weijian Chen , Na Cheng , Jingyuan Xu , Dong Li , Hongyu Wang

Aspect oriented programming aims at achieving better modularization for a system's crosscutting concerns in order to improve its key quality attributes, such as evolvability and reusability. Consequently, the adoption of aspect-oriented…

Software Engineering · Computer Science 2016-08-31 Arie van Deursen , Marius Marin , Leon Moonen