Publications associées à Further Collapses in TFNP

Further Collapses in TFNP

Gilbert Théodore Maystre, Ran Tao, Mika Tapani Göös, Siddhartha Jain, Alexandros Paul Hollender

We show EOPL = PLS \cap PsansP \sansP AD. Here the class EOPL consists of all total search problems that reduce to the END -OF -POTENTIAL -LINE problem, which was introduced in the works by Hub'acv \ek and Yogev (SICOMP 2020) and Fearnley et al. (JCSS 202 ...

Siam Publications2024

Approximation Algorithms for Allocation and Network Design

Etienne Michel François Bamas

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

EPFL2023

Proofs, Circuits, and Communication

Mika Tapani Göös

We survey lower-bound results in complexity theory that have been obtained via newfound interconnections between propositional proof complexity, boolean circuit complexity, and query/communication complexity. We advocate for the theory of total search prob ...

2022

Hybrid Flock - Formation Control Algorithms

Alcherio Martinoli, Cyrill Silvan Baumann, Jonas Perolini, Emna Tourki

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

Springer Nature Switzerland2022

Minimum Cost Intervention Design for Causal Effect Identification

Seyed Jalal Etesami, Negar Kiyavash, Sina Akbari

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the ...

PMLR2022

Sketches, metrics and fast algorithms

Navid Nouri

As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

EPFL2022

Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds

Adam Teodor Polak, Marek Elias

We study the online problem of minimizing power consumption in systems with multiple power-saving states. During idle periods of unknown lengths, an algorithm has to choose between power-saving states of different energy consumption and wake-up costs. We d ...

2021

A note on the integrality gap of the configuration LP for restricted Santa Claus

Klaus Jansen, Lars Rohwedder

In the restricted Santa Claus problem we are given resources R and players P. Every resource j is an element of R. has a value v(j) and every player i is an element of P desires a set of resources R(i). We are interested in distributing the resources to pl ...

ELSEVIER2020

A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain

Fernando Porté Agel, Roberto Brogna

Layout optimization of wind farms constitutes an important and challenging task in complex terrain. This is especially due to the complex interactions of the boundary layer flows in complex terrain and wind turbine wakes, which renders wake modelling in co ...

ELSEVIER SCI LTD2020

Heterogeneous Target Assignment to Robotic Fiber Positioner Systems

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

The target assignment methods applied to robotic fiber positioners are only applicable to homogeneous sets of targets to be observed. However, different batches of robotic fiber positioners available at the focal plane of a telescope can be simultaneously ...

IEEE2019

Scaling Functional Synthesis and Repair

Emmanouil Koukoutos

Program synthesis was first proposed a few decades ago, but in the last decade it has gained increased momentum in the research community. The increasing complexity of software has dictated the urgent need for improved supporting tools that verify the soft ...

EPFL2019

An Optimal Planning Framework to Deploy Self-Reconfigurable Modular Robots

Auke Ijspeert, Alexandre Bernardino, Mehmet Hasan Mutlu, Simon Lukas Hauser, Hala Khodr

Self-reconfiguration is a hard problem due to the high dimensionality of self-reconfigurable modular systems. Searchbased approaches offer complete and optimal solutions. However, naive search algorithms cannot directly solve self-reconfiguration tasks in ...

2019

New Graph Algorithms via Polyhedral Techniques

Jakub Tarnawski

In this thesis we give new algorithms for two fundamental graph problems. We develop novel ways of using linear programming formulations, even exponential-sized ones, to extract structure from problem instances and to guide algorithms in making progress. S ...

EPFL2019

Scalable Convex Optimization Methods for Semidefinite Programming

Alp Yurtsever

With the ever-growing data sizes along with the increasing complexity of the modern problem formulations, contemporary applications in science and engineering impose heavy computational and storage burdens on the optimization algorithms. As a result, there ...

EPFL2019

Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior

Boi Faltings, Panayiotis Danassis, Aris Filos Ratsikas

We present a novel anytime heuristic (ALMA), inspired by the human principle of altruism, for solving the assignment problem. ALMA is decentralized, completely uncoupled, and requires no communication between the participants. We prove an upper bound on th ...

2019

New Algorithmic Paradigms for Discrete Problems using Dynamical Systems and Polynomials

Damian Mateusz Straszak

Optimization is a fundamental tool in modern science. Numerous important tasks in biology, economy, physics and computer science can be cast as optimization problems. Consider the example of machine learning: recent advances have shown that even the most s ...

EPFL2018

On flexible Green function methods for atomistic/continuum coupling

Max Ludwig Hodapp

Atomistic/continuum (A/C) coupling schemes have been developed during the past twenty years to overcome the vast computational cost of fully atomistic models, but have not yet reached full maturity to address many problems of practical interest. This work ...

EPFL2018

Novel Algorithms For Clustering

James Peter Newling

Clustering is a method for discovering structure in data, widely used across many scientific disciplines. The two main clustering problems this dissertation considers are K-means and K-medoids. These are NP-hard problems in the number of samples and cluste ...

EPFL2018

Algorithms For Clustering Problems : Theoretical Guarantees and Empirical Evaluations

Ashkan Norouzi Fard

Clustering is a classic topic in combinatorial optimization and plays a central role in many areas, including data science and machine learning. In this thesis, we first focus on the dynamic facility location problem (i.e., the facility location problem in ...

EPFL2018

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Volkan Cevher, Ilija Bogunovic, Slobodan Mitrovic, Ashkan Norouzi Fard, Jakub Tarnawski

We study the classical problem of maximizing a monotone submodular function subject to a cardinality constraint k, with two additional twists: (i) elements arrive in a streaming fashion and (ii) m items from the algorithm’s memory might be removed after th ...

2017