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Learning Sparse Graphons And The Generalized Kesten-Stigum Threshold

Emmanuel Abbé

The problem of learning graphons has attracted considerable attention across several scientific communities, with significant progress over the re-cent years in sparser regimes. Yet, the current techniques still require diverg-ing degrees in order to succe ...

INST MATHEMATICAL STATISTICS-IMS2023

How to Find Molecules with Long-lasting Charge Migration?

Jiri Vanicek, Alan Scheidegger, Nikolay Golubev

Under certain conditions, the ionization of a molecule may create a superposition of electronic states, leading to ultrafast electron dynamics. If controlled, this motion could be used in attochemistry applications, but it has been shown that the decoheren ...

SWISS CHEMICAL SOC2023

Efficient Preparation of Cyclic Quantum States

Giovanni De Micheli, Fereshte Mozafari Ghoraba

Universal quantum algorithms that prepare arbitrary n-qubit quantum states require O(2n) gate complexity. The complexity can be reduced by considering specific families of quantum states depending on the task at hand. In particular, multipartite quantum st ...

IEEE2022

Safety Verification for Urban Air Mobility Scheduling

Nils Gustav Nilsson

In Urban Air Mobility (UAM) networks, takeoff and landing sites, called vertiports, are likely to experience intermittent closures due to, e.g., adverse weather. For safety, it will be required that all in-transit Urban Air Vehicles (UAVs) in a UAM network ...

ELSEVIER2022

Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

Giovanni De Micheli, Massimiliano Di Ventra

As demands for computing have been continuously increasing, various solutions have been proposed. Some approaches deal with improving algorithms and software programs, mainly through the tuning of advanced heuristics and learning methods. Some other tackle ...

2020

A Catalyst Framework for Minimax Optimization

Negar Kiyavash

We introduce a generic two-loop scheme for smooth minimax optimization with strongly-convex-concave objectives. Our approach applies the accelerated proximal point framework (or Catalyst) to the associated dual problem and takes full advantage of existing ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2020

Asymptotically Optimal Contextual Bandit Algorithm Using Hierarchical Structures

Hakan Gökcesu, Kaan Gökcesu

We propose an online algorithm for sequential learning in the contextual multiarmed bandit setting. Our approach is to partition the context space and, then, optimally combine all of the possible mappings between the partition regions and the set of bandit ...

2019

Monogenic Filtering Based Automatic Defect Detection from a Single Fringe Pattern

Pramod Rastogi, Rishikesh Dilip Kulkarni

We propose a fringe analysis algorithm for the automatic detection of defects from a single fringe pattern (FP). Typically, the surface defects exhibit high fringe density areas in the FP. Consequently, high fringe density regions can be utilized as a sign ...

Springer, Cham2019

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Juri Ranieri, Gilles Baechler, Amina Chebira, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

When Stuck, Flip a Coin

Slobodan Mitrovic

Many modern services need to routinely perform tasks on a large scale. This prompts us to consider the following question: How can we design efficient algorithms for large-scale computation? In this thesis, we focus on devising a general strategy to addr ...

EPFL2018