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Planning for legged-wheeled machines is typically done using trajectory optimization because of many degrees of freedom, thus rendering legged-wheeled planners prone to falling prey to bad local minima. We present a combined sampling and…

Robotics · Computer Science 2021-04-12 Edo Jelavic , Farbod Farshidian , Marco Hutter

The design of an electrical machine can be quantified and evaluated by Key Performance Indicators (KPIs) such as maximum torque, critical field strength, costs of active parts, sound power, etc. Generally, cross-domain tool-chains are used…

Machine Learning · Computer Science 2021-01-26 Vivek Parekh , Dominik Flore , Sebastian Schöps

Metric data structures (distance oracles, distance labeling schemes, routing schemes) and low-distortion embeddings provide a powerful algorithmic methodology, which has been successfully applied for approximation algorithms \cite{llr},…

Data Structures and Algorithms · Computer Science 2015-04-08 Michael Elkin , Arnold Filtser , Ofer Neiman

The development of smart grids has effectively transformed the traditional grid system. This promises numerous advantages for economic values and autonomous control of energy sources. In smart grids development, there are various objectives…

Systems and Control · Electrical Eng. & Systems 2019-10-22 Kayode Adetunji , Ivan Hofsajer , Ling Cheng

Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-differentiability, and unknown model order. Existing approaches often struggle with local…

Machine Learning · Computer Science 2026-05-28 Zhiqin Cheng , Yu Zhan , Mingjin Zhang , Lingbo Liu , Liang Lin

Over the past decade, decision diagrams (DDs) have been used to model and solve integer programming and combinatorial optimization problems. Despite successful performance of DDs in solving various discrete optimization problems, their…

Optimization and Control · Mathematics 2024-03-27 Hosseinali Salemi , Danial Davarnia

We analyze integer linear programs which we obtain after discretizing two-dimensional subproblems arising from a trust-region algorithm for mixed integer optimal control problems with total variation regularization. We discuss NP-hardness…

Optimization and Control · Mathematics 2025-03-07 Paul Manns , Marvin Severitt

In [Q. Liao et al., Commun. Math. Sci., 20(2022)], a linear-time Sinkhorn algorithm is developed based on dynamic programming, which significantly reduces the computational complexity involved in solving optimal transport problems. However,…

Optimization and Control · Mathematics 2025-03-25 Ziyuan Lyu , Zihao Wang , Hao Wu , Shuai Yang

It is well known that selecting a good Mixed Integer Programming (MIP) formulation is crucial for an effective solution with state-of-the art solvers. While best practices and guidelines for constructing good formulations abound, there is…

Optimization and Control · Mathematics 2017-05-23 Juan Pablo Vielma

A wide range of decision problems can be formulated as bilevel programs with independent followers, which as a special case include two-stage stochastic programs. These problems are notoriously difficult to solve especially when a large…

Optimization and Control · Mathematics 2025-09-25 Timothy C. Y. Chan , Bo Lin , Shoshanna Saxe

Recent years have seen significant advances in quantum/quantum-inspired technologies capable of approximately searching for the ground state of Ising spin Hamiltonians. The promise of leveraging such technologies to accelerate the solution…

Optimization and Control · Mathematics 2024-01-24 Robin Brown , David E. Bernal Neira , Davide Venturelli , Marco Pavone

The robust truss topology optimization against the uncertain static external load can be formulated as mixed-integer semidefinite programming. Although a global optimal solution can be computed with a branch-and-bound method, it is very…

Optimization and Control · Mathematics 2019-01-25 Yoshihiro Kanno

We propose a novel method to enhance the performance of coordinate-MLPs by learning instance-specific positional embeddings. End-to-end optimization of positional embedding parameters along with network weights leads to poor generalization…

Machine Learning · Computer Science 2022-03-22 Sameera Ramasinghe , Simon Lucey

The vast majority of mesh-based modelling applications iteratively transform the mesh vertices under prescribed geometric conditions. This occurs in particular in methods cycling through the constraint set such as Position-Based Dynamics…

Numerical Analysis · Mathematics 2020-11-25 Carlos Arango Duque , Adrien Bartoli

We introduce a family of numerical algorithms for the solution of linear system in higher dimensions with the matrix and right hand side given and the solution sought in the tensor train format. The proposed methods are rank--adaptive and…

Numerical Analysis · Mathematics 2014-10-07 Sergey V. Dolgov , Dmitry V. Savostyanov

Placement Optimization is an important problem in systems and chip design, which consists of mapping the nodes of a graph onto a limited set of resources to optimize for an objective, subject to constraints. In this paper, we start by…

Artificial Intelligence · Computer Science 2020-03-20 Anna Goldie , Azalia Mirhoseini

We propose a model-based, automated, bottom-up approach for design, which is applicable to various physical domains, but in this work we focus on the electrical domain. This bottom-up approach is based on a meta-topology in which each link…

Optimization and Control · Mathematics 2023-02-17 Ion Matei , Maksym Zhenirovskyy , John Maxwell , Johan de Kleer

In this paper, we introduce new stable mixed finite elements of any order on polytopal mesh for solving second order elliptic problem. We establish optimal order error estimates for velocity and super convergence for pressure. Numerical…

Numerical Analysis · Mathematics 2020-09-14 Yanping Lin , Xiu Ye , Shangyou Zhang

The transition to Electric Vehicles (EVs) demands intelligent, congestion-aware infrastructure planning to balance user convenience, economic viability, and traffic efficiency. We present a joint optimisation framework for EV Charging…

Multiagent Systems · Computer Science 2026-03-24 Niloofar Aminikalibar , Farzaneh Farhadi , Maria Chli

Many complex robotic manipulation tasks can be decomposed as a sequence of pick and place actions. Training a robotic agent to learn this sequence over many different starting conditions typically requires many iterations or demonstrations,…

Robotics · Computer Science 2024-03-19 Haojie Huang , Owen Howell , Dian Wang , Xupeng Zhu , Robin Walters , Robert Platt