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A new constructive heuristic driven by machine learning for the traveling salesman problem

Mele, Umberto Junior ; Gambardella, Luca Maria ; Montemanni, Roberto

In: Algorithms, 2021, vol. 14, no. 9, p. 25

Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be...

Demystifying Artificial Intelligence

Mondal, Manuel ; Lalanne, Denis

(Internal working papers DIUF ; 21-02)

The objective of this document is to provide a non-technical introduction to the field of Artificial Intelligence. It is intended for anyone outside of the data science community curi-ous about the subject, such as researchers from other areas looking for new instruments, legal professionals confronted with automated decision making algorithms or legal tech tools, en-trepreneurs interested in...

Testing for symmetry and conditional symmetry using asymmetric kernels

Fernandes, Marcelo ; Mendes, Eduardo ; Scaillet, Olivier

In: Annals of the Institute of Statistical Mathematics, 2015, vol. 67, no. 4, p. 649-671

Shared neural basis of social and non-social reward deficits in chronic cocaine users

Tobler, Philippe N. ; Preller, Katrin H. ; Campbell-Meiklejohn, Daniel K. ; Kirschner, Matthias ; Kraehenmann, Rainer ; Stämpfli, Philipp ; Herdener, Marcus ; Seifritz, Erich ; Quednow, Boris B.

In: Social Cognitive and Affective Neuroscience, 2016, vol. 11, no. 6, p. 1017-1025

Heat kernels on regular graphs and generalized Ihara zeta function formulas

Chinta, G. ; Jorgenson, J. ; Karlsson, A.

In: Monatshefte für Mathematik, 2015, vol. 178, no. 2, p. 171-190

Dictionary Learning for Fast Classification Based on Soft-thresholding

Fawzi, Alhussein ; Davies, Mike ; Frossard, Pascal

In: International Journal of Computer Vision, 2015, vol. 114, no. 2-3, p. 306-321

Kernelized rank learning for personalized drug recommendation

He, Xiao ; Folkman, Lukas ; Borgwardt, Karsten ; Wren, Jonathan ; Wren, Jonathan

In: Bioinformatics, 2018, vol. 34, no. 16, p. 2808-2816

NMR structure calculation for all small molecule ligands and non-standard residues from the PDB Chemical Component Dictionary

Yilmaz, Emel ; Güntert, Peter

In: Journal of Biomolecular NMR, 2015, vol. 63, no. 1, p. 21-37

Neuralink and Beyond: Challenges of Creating an Enhanced Human

Gurtner, Dimitri

(Internal working papers DIUF ; 21-01)

This article is a literature review of Neuralink, brain-machine interfaces (BMIs) and their applications, followed by future possibilities of BMIs and their potential impacts. Currently, BMIs predominantly have therapeutic applications, such as helping people with spinal cord injury by allowing them to control a computer directly with their brain. However, BMIs can also improve learning,...

Including Covariates in the Regression Discontinuity Design

Frölich, Markus ; Huber, Martin

In: Journal of Business and Economic Statistics, 2019, vol. 37, no. 4, p. 736-748

This article proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the treatment effect at the rate of one- dimensional nonparametric regression, irrespective of the...