Publications related to Scalable Stochastic Optimization: Scenario Reduction with Guarantees

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

or

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

Andreas Loukas, Nikolaos Karalias

Combinatorial optimization (CO) problems are notoriously challenging for neural networks, especially in the absence of labeled instances. This work proposes an unsupervised learning framework for CO problems on graphs that can provide integral solutions of ...

2020

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

Hossein Sekhavatmanesh

The distribution network restoration problem is by nature a mixed integer and non-linear optimization problem due to the switching decisions and Optimal Power Flow (OPF) constraints, respectively. The link between these two parts involves logical implicati ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Variational Inference with Mixture Model Approximation for Applications in Robotics

Sylvain Calinon, Emmanuel Pignat, Teguh Santoso Lembono

We propose to formulate the problem of repre-senting a distribution of robot configurations (e.g. joint angles)as that of approximating a product of experts. Our approach uses variational inference, a popular method in Bayesian computation, which has sever ...

2020

A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration

François Maréchal, Ivan Daniel Kantor, Hür Ebuzer Bütün

This research presents a mathematical formulation for optimizing integration of complex industrial systems from the level of unit operations to processes, entire plants, and finally to considering industrial symbiosis opportunities between plants. The fram ...

2020

Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations

Martin Jaggi, Aymeric Daphnis Kévin Dieuleveut, Sidak Pal Singh, Andreas Hug

We present a framework for building unsupervised representations of entities and their compositions, where each entity is viewed as a probability distribution rather than a vector embedding. In particular, this distribution is supported over the contexts w ...

ADDISON-WESLEY PUBL CO2020

Fair Colorful k-Center Clustering

Ola Nils Anders Svensson, Xinrui Jia

An instance of colorful k-center consists of points in a metric space that are colored red or blue, along with an integer k and a coverage requirement for each color. The goal is to find the smallest radius ρ such that there exist balls of radius ρ around ...

Springer2020

Multimodal water age distributions and the challenge of complex hydrological landscapes

Paolo Benettin

Travel time distributions (TTDs) are concise descriptions of transport processes in catchments based on water ages, and they are particularly efficient as lumped hydrological models to simulate tracers in outflows. Past studies have approximated catchment ...

2020

Distributionally Robust Mechanism Design

Daniel Kuhn, Cagil Kocyigit, Wolfram Wiesemann

We study a mechanism design problem where an indivisible good is auctioned to multiple bidders, for each of whom it has a private value that is unknown to the seller and the other bidders. The agents perceive the ensemble of all bidder values as a random v ...

2020

Redundant features can hurt robustness to distributions shift

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Guillermo Ortiz Jimenez, Apostolos Modas

In this work, we borrow tools from the field of adversarial robustness, and propose a new framework that permits to relate dataset features to the distance of samples to the decision boundary. Using this framework we identify the subspace of features used ...

2020

Scalable Stochastic Optimization: Scenario Reduction with Guarantees

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Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

Variational Inference with Mixture Model Approximation for Applications in Robotics

A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration

Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations

Fair Colorful k-Center Clustering

Multimodal water age distributions and the challenge of complex hydrological landscapes

Distributionally Robust Mechanism Design

Redundant features can hurt robustness to distributions shift

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

Multimodal water age distributions and the challenge of complex hydrological landscapes

Variational Inference with Mixture Model Approximation for Applications in Robotics

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

Redundant features can hurt robustness to distributions shift

Fair Colorful k-Center Clustering

Distributionally Robust Mechanism Design

Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations

A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration