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Equality between Monge and Kantorovich multimarginal problems with Coulomb cost

Publications associées (34)

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Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling

Robert West, Maxime Jean Julien Peyrard, Marija Sakota

Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

Assoc Computing Machinery2024

Efficient Online Clustering with Moving Costs

Volkan Cevher, Efstratios Panteleimon Skoulakis

In this work we consider an online learning problem, called Online k-Clustering with Moving Costs, at which a learner maintains a set of k facilities over T rounds so as to minimize the connection cost of an adversarially selected sequence of clients. The ...

2023

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization ...

SPRINGER HEIDELBERG2022

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

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paper studies exploiting action-level learning (imitation) in the optimal control problem context. Cost functions defined by the optimal control methods are similar to the goal-level learning (emulation) in animals. However, imitating the robot's or others ...

IEEE2021

Cost and benefit allocation in a energy community

In the transition to a sustainable energy system, energy communities have unique advantages; they require no additional land and allow inhabitants to reduce their energy bills. Nowadays, each shareholder’s profit is calculated based on their share of inves ...

2021

Minimizing Regret of Bandit Online Optimization in Unconstrained Action Spaces

Maryam Kamgarpour

We consider online convex optimization with a zero-order oracle feedback. In particular, the decision maker does not know the explicit representation of the time-varying cost functions, or their gradients. At each time step, she observes the value of the c ...

2020

Coordinate Descent with Bandit Sampling

Patrick Thiran, Laura Elisa Celis, Farnood Salehi

Coordinate descent methods usually minimize a cost function by updating a random decision variable (corresponding to one coordinate) at a time. Ideally, we would update the decision variable that yields the largest decrease in the cost function. However, f ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Minimizing Regret in Unconstrained Online Convex Optimization

Maryam Kamgarpour

We consider online convex optimizations in the bandit setting. The decision maker does not know the time- varying cost functions, or their gradients. At each time step, she observes the value of the cost function for her chosen action. The objective is to ...

IEEE2018

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This paper presents the first application to real JET data of the new equilibrium code NICE which enables the consistent resolution of the inverse equilibrium reconstruction problem in the framework of non-linear free-boundary equilibrium coupled to the St ...

IOP PUBLISHING LTD2018