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Publications associées (28)

Shrinking FPGA Static Power via Machine Learning-Based Power Gating and Enhanced Routing

Mirjana Stojilovic, Hossein Asadi, Zeinab Seifoori

Despite FPGAs rapidly evolving to support the requirements of the most demanding emerging applications, their high static power consumption, concentrated within the routing resources, still presents a major hurdle for low-power applications. Augmenting the ...

2021

Data reduction for mixed integer linear programming in complex energy systems

François Maréchal, Luc Girardin, Julia Granacher, Luise Middelhauve, Natalija Ljubic

The task of optimally designing and scheduling energy systems with a high share of renewable energies is complex and computationally demanding. A widespread method for tackling this task is to apply mixed integer linear programming (MILP). Even though the ...

2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Pierre Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

Knapsack and Subset Sum with Small Items

Adam Teodor Polak, Lars Rohwedder

Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In t ...

Schloss Dagstuhl -- Leibniz-Zentrum für Informatik2021

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Ahmet Alacaoglu

Stochastic gradient descent (SGD) and randomized coordinate descent (RCD) are two of the workhorses for training modern automated decision systems. Intriguingly, convergence properties of these methods are not well-established as we move away from the spec ...

EPFL2021

Optimal Policies for Age and Distortion in a Discrete-Time Model

Emre Telatar, Yunus Inan, Reka Inovan

We propose a simple model to study the tradeoff between timeliness and distortion, where different pieces of data have a different cost of not being sent. We pose the question of finding the optimal tradeoff as a policy design problem amenable to dynamic p ...

IEEE2021

Recursive blocked algorithms for linear systems with Kronecker product structure

Daniel Kressner

Recursive blocked algorithms have proven to be highly efficient at the numerical solution of the Sylvester matrix equation and its generalizations. In this work, we show that these algorithms extend in a seamless fashion to higher-dimensional variants of g ...

SPRINGER2020

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed for understanding how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment with a swarm of drones over a de ...

2020

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