Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Kaarthik P"'
The article develops a parametric model of fairness called "$\varepsilon$-fairness" that can be represented using a single second-order cone constraint and incorporated into existing decision-making problem formulations without impacting the complexi
Externí odkaz:
http://arxiv.org/abs/2412.05143
Autor:
Srinivasan, Shriram, Sundar, Kaarthik
Potential-driven steady-state flow in networks is an abstract problem which manifests in various engineering applications, such as transport of natural gas, water, electric power through infrastructure networks or flow through fractured rocks modeled
Externí odkaz:
http://arxiv.org/abs/2410.19850
Autor:
Bain, Nicolas, Wilen, Lawrence A., Gerber, Dominic, Zu, Mengjie, Goodrich, Carl P., Duraivel, Senthilkumar, Varma, Kaarthik, Koganti, Harsha, Style, Robert W., Dufresne, Eric R.
The softer a material is, the more its mechanics are sensitive to interfaces. In soft gels, an elastic polymeric network is filled with free-flowing molecules. In theory, either of these components could dominate the material interfacial properties.
Externí odkaz:
http://arxiv.org/abs/2410.09158
Constrained optimization problems arise in various engineering system operations such as inventory management and electric power grids. However, the requirement to repeatedly solve such optimization problems with uncertain parameters poses a signific
Externí odkaz:
http://arxiv.org/abs/2410.03085
Autor:
Sundar, Kaarthik, Rathinam, Sivakumar
We present a novel algorithm that fuses the existing convex-programming based approach with heuristic information to find optimality guarantees and near-optimal paths for the Shortest Path Problem in the Graph of Convex Sets (SPP-GCS). Our method, in
Externí odkaz:
http://arxiv.org/abs/2407.17413
Autor:
Kim, Hyejin, Zhou, Yiqing, Xu, Yichen, Varma, Kaarthik, Karamlou, Amir H., Rosen, Ilan T., Hoke, Jesse C., Wan, Chao, Zhou, Jin Peng, Oliver, William D., Lensky, Yuri D., Weinberger, Kilian Q., Kim, Eun-Ah
The imminent era of error-corrected quantum computing urgently demands robust methods to characterize complex quantum states, even from limited and noisy measurements. We introduce the Quantum Attention Network (QuAN), a versatile classical AI framew
Externí odkaz:
http://arxiv.org/abs/2405.11632
We examine the modeling, simulation, and optimization of district heating systems, which are widely used for thermal transport using steam or hot water as a carrier. We propose a generalizable framework to specify network models and scenario paramete
Externí odkaz:
http://arxiv.org/abs/2404.18868
The Multiple Traveling Salesman Problem (MTSP) with a single depot is a generalization of the well-known Traveling Salesman Problem (TSP) that involves an additional parameter, namely, the number of salesmen. In the MTSP, several salesmen at the depo
Externí odkaz:
http://arxiv.org/abs/2404.08157
Autor:
Mishra, Manav, Bana, Hritik, Sarkar, Saswata, Sanjeevi, Sujeevraja, Sujit, PB, Sundar, Kaarthik
This article presents a deep reinforcement learning-based approach to tackle a persistent surveillance mission requiring a single unmanned aerial vehicle initially stationed at a depot with fuel or time-of-flight constraints to repeatedly visit a set
Externí odkaz:
http://arxiv.org/abs/2404.06423
Natural gas consumption by users of pipeline networks is subject to increasing uncertainty that originates from the intermittent nature of electric power loads serviced by gas-fired generators. To enable computationally efficient optimization of gas
Externí odkaz:
http://arxiv.org/abs/2403.18124