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1. Approximation in a Cubic Super-Spline Space

Author

Barrera, D., Eddargani, S., Lamnii, A., Castro, Carlos, Editor-in-Chief, Formaggia, Luca, Editor-in-Chief, Groppi, Maria, Series Editor, Larson, Mats G., Series Editor, Lopez Fernandez, Maria, Series Editor, Morales de Luna, Tomás, Series Editor, Pareschi, Lorenzo, Series Editor, Vázquez-Cendón, Elena, Series Editor, Zunino, Paolo, Series Editor, Sbibih, Driss, editor, Remogna, Sara, editor, and Serghini, Abdelhafid, editor

Published
2024
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2. Statistical Learning of Value-at-Risk and Expected Shortfall

Author

Barrera, D, Crépey, S, Gobet, E, Nguyen, Hoang-Dung, and Saadeddine, B

Subjects
Quantitative Finance - Computational Finance, Statistics - Machine Learning
Abstract

We propose a non-asymptotic convergence analysis of a two-step approach to learn a conditional value-at-risk (VaR) and a conditional expected shortfall (ES) using Rademacher bounds, in a non-parametric setup allowing for heavy-tails on the financial loss. Our approach for the VaR is extended to the problem of learning at once multiple VaRs corresponding to different quantile levels. This results in efficient learning schemes based on neural network quantile and least-squares regressions. An a posteriori Monte Carlo procedure is introduced to estimate distances to the ground-truth VaR and ES. This is illustrated by numerical experiments in a Student-$t$ toy model and a financial case study where the objective is to learn a dynamic initial margin.

Published
2022

13. Anger and disgust shape judgments of social sanctions across cultures, especially in high individual autonomy societies

Author

Andersson, P. A., Vartanova, I., Västfjäll, D., Tinghög, G., Strimling, P., Wu, J., Hazin, I., Akotia, C. S., Aldashev, A., Andrighetto, Giulia, Anum, A., Arikan, G., Bagherian, F., Barrera, D., Basnight-Brown, D., Batkeyev, B., Berezina, E., Björnstjerna, M., Boski, P., Bovina, I., Huyen, B. T. T., Čekrlija, Đ., Choi, H. -S, Contreras-Ibáñez, C. C., Costa-Lopes, R., de Barra, M., de Zoysa, P., Dorrough, A. R., Dvoryanchikov, N., Engelmann, J. B., Euh, H., Fang, X., Fiedler, S., Foster-Gimbel, O. A., Fülöp, M., Gardarsdottir, R. B., Gill, C. M. H. D., Glöckner, A., Graf, S., Grigoryan, A., Gritskov, V., Growiec, K., Halama, P., Hartanto, A., Hopthrow, T., Hřebíčková, M., Iliško, D., Imada, H., Kapoor, H., Kawakami, K., Khachatryan, N., Kharchenko, N., Kiyonari, T., Kohút, M., Leslie, L. M., Li, Y., Li, N. P., Li, Z., Liik, K., Maitner, A. T., Manhique, B., Manley, H., Medhioub, I., Mentser, S., Nejat, P., Nipassa, O., Nussinson, R., Onyedire, N. G., Onyishi, I. E., Panagiotopoulou, P., Perez-Floriano, L. R., Persson, M., Pirttilä-Backman, A. -M, Pogosyan, M., Raver, J., Rodrigues, R. B., Romanò, S., Romero, P. P., Sakki, I., San Martin, A., Sherbaji, S., Shimizu, H., Simpson, B., Szabo, E., Takemura, K., Teixeira, M. L. M., Thanomkul, N., Tiliouine, H., Travaglino, G. A., Tsirbas, Y., Widodo, S., Zein, R., Zirganou-Kazolea, L., Eriksson, K., Andersson, P. A., Vartanova, I., Västfjäll, D., Tinghög, G., Strimling, P., Wu, J., Hazin, I., Akotia, C. S., Aldashev, A., Andrighetto, Giulia, Anum, A., Arikan, G., Bagherian, F., Barrera, D., Basnight-Brown, D., Batkeyev, B., Berezina, E., Björnstjerna, M., Boski, P., Bovina, I., Huyen, B. T. T., Čekrlija, Đ., Choi, H. -S, Contreras-Ibáñez, C. C., Costa-Lopes, R., de Barra, M., de Zoysa, P., Dorrough, A. R., Dvoryanchikov, N., Engelmann, J. B., Euh, H., Fang, X., Fiedler, S., Foster-Gimbel, O. A., Fülöp, M., Gardarsdottir, R. B., Gill, C. M. H. D., Glöckner, A., Graf, S., Grigoryan, A., Gritskov, V., Growiec, K., Halama, P., Hartanto, A., Hopthrow, T., Hřebíčková, M., Iliško, D., Imada, H., Kapoor, H., Kawakami, K., Khachatryan, N., Kharchenko, N., Kiyonari, T., Kohút, M., Leslie, L. M., Li, Y., Li, N. P., Li, Z., Liik, K., Maitner, A. T., Manhique, B., Manley, H., Medhioub, I., Mentser, S., Nejat, P., Nipassa, O., Nussinson, R., Onyedire, N. G., Onyishi, I. E., Panagiotopoulou, P., Perez-Floriano, L. R., Persson, M., Pirttilä-Backman, A. -M, Pogosyan, M., Raver, J., Rodrigues, R. B., Romanò, S., Romero, P. P., Sakki, I., San Martin, A., Sherbaji, S., Shimizu, H., Simpson, B., Szabo, E., Takemura, K., Teixeira, M. L. M., Thanomkul, N., Tiliouine, H., Travaglino, G. A., Tsirbas, Y., Widodo, S., Zein, R., Zirganou-Kazolea, L., and Eriksson, K.

Abstract

When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions., Article; Export Date: 20 March 2024; Cited By: 0; Correspondence Address: P.A. Andersson; Department of Behavioral Sciences and Learning, Linköping University, Linköping, 581 83, Sweden; email: per.a.andersson@liu.se

Published
2024
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14. Enhancement of the sensitivity of a temperature sensor based on Fiber Bragg Gratings via weak value amplification

Author

Salazar-Serrano, L. J., Barrera, D., Amaya, W., Sales, S., Pruneri, V., and Torres, J. P.

Subjects
Quantum Physics, Physics - Optics
Abstract

We present a proof-of-concept experiment aimed at increasing the sensitivity of temperature sensors implemented with Fiber Bragg gratings by making use of a weak value amplification scheme. The technique requires only linear optics elements for its implementation, and appears as a promising method for extending the range of temperatures changes detectable to increasingly lower values than state-of the-art sensors can currently provide. The device implemented here is able to generate a shift of the centroid of the spectrum of a pulse of $\mathrm{\sim 0.035\,nm/^{\circ}C}$, a nearly fourfold increase in sensitivity over the same Fiber Bragg Grating system interrogated using standard methods., Comment: 4 pages, 4 figures

Published
2015
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19. Near-best univariate spline discrete quasi-interpolants on non-uniform partitions

Author

Barrera, D., Ibanez, M. J., Sablonniere, Paul, and Sbibih, D.

Subjects
Mathematics - Numerical Analysis, 41A15, 41A35, 65D07, 65D17
Abstract

Univariate spline discrete quasi-interpolants (abbr. dQIs) are approximation operators using B-spline expansions with coefficients which are linear combinations of discrete values of the function to be approximated. When working with nonuniform partitions, the main challenge is to find dQIs which have both good approximation orders and bounded uniform norms independent of the given partition. Near-best dQIs are obtained by minimizing an upper bound of the infinite norm of dQIs depending on a certain number of free parameters, thus reducing this norm. This paper is devoted to the study of some families of near-best dQIs of approximation order 2.

Published
2004

33. Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective

Author

Ministerio de Ciencia, Innovación y Universidades (España), Maldonado, D., Aldana, S., González Bargalló, Mireia, Jiménez-Molinos, F., Ibáñez, M. J., Barrera, D., Campabadal Segura, Francesca, Roldán, J. B., Ministerio de Ciencia, Innovación y Universidades (España), Maldonado, D., Aldana, S., González Bargalló, Mireia, Jiménez-Molinos, F., Ibáñez, M. J., Barrera, D., Campabadal Segura, Francesca, and Roldán, J. B.

Abstract

We have analyzed variability in resistive memories (Resistive Random Access Memories, RRAMs) making use of advanced numerical techniques to process experimental measurements and simulations based on the kinetic Monte Carlo technique. The devices employed in the study were fabricated using the TiN/Ti/HfO2/W stack. The switching parameters were obtained making use of new developed extraction methods. The appropriateness of the advanced parameter extraction methodologies has been checked by comparison to kinetic Monte Carlo simulations; in particular, the reset and set events have been studied and detected. The data obtained were employed to shed light on the resistive switching operation and the cycle-to-cycle variability. It has been shown that variability depends on the numerical technique employed to obtain the set and reset voltages, therefore, this issue must be taken into consideration in RS characterization and modeling studies. The proposed techniques are complementary and depending on the technology and the curves shape the features of a particular method could make it to be the most appropriate.

Published
2022

37. Learning Value-at-Risk and Expected Shortfall *

Author

Barrera, D, Crépey, S, Gobet, E, Nguyen, Hoang-Dung, Saadeddine, B, Crépey, Stéphane, Universidad de los Andes [Bogota] (UNIANDES), Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université Paris Cité (UPCité), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), École polytechnique (X), Université Paris-Saclay, Natixis, Université d'Évry-Val-d'Essonne (UEVE), and Crédit Agricole

Subjects
FOS: Computer and information sciences, quantile regression, quantile crossings, 91G60, Computational Finance (q-fin.CP), Machine Learning (stat.ML), neural networks, [QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP], [STAT] Statistics [stat], FOS: Economics and business, Quantitative Finance - Computational Finance, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, 2G32, value-at-risk expected shortfall quantile regression quantile crossings neural networks AMS Subject Classification: 62G32 62L20 62M45 91G60 91G70, 62M45, value-at-risk, 91G70, expected shortfall, 62L20
Abstract

We propose a non-asymptotic convergence analysis of a two-step approach to learn a conditional value-at-risk (VaR) and expected shortfall (ES) in a nonparametric setting using Rademacher and Vapnik-Chervonenkis bounds. Our approach for the VaR is extended to the problem of learning at once multiple VaRs corresponding to different quantile levels. This results in efficient learning schemes based on neural network quantile and least-squares regressions. An a posteriori Monte Carlo (non-nested) procedure is introduced to estimate distances to the ground-truth VaR and ES without access to the latter. This is illustrated using numerical experiments in a Gaussian toy-model and a financial case-study where the objective is to learn a dynamic initial margin.

Published
2022

43. ask the Brains

Author

Barrera, D. and Bogaerts, T.

Published
2006

47. Author correction: Perceptions of the appropriate response to norm violation in 57 societies

Author

Eriksson, K., Strimling, P., Gelfand, M., Wu, J., Abernathy, J., Akotia, C., Aldashev, A., Andersson, P., Andrighetto, G., Anum, A., Arikan, G., Aycan, Z., Bagherian, F., Barrera, D., Basnight-Brown, D., Batkeyev, B., Belaus, A., Berezina, E., Björnstjerna, M., Blumen, S., Boski, P., Zeineddine, F., Bovina, I., Huyen, B., Cardenas, J., Čekrlija, Đ., Choi, H., Contreras-Ibáñez, C., Costa-Lopes, R., de Barra, M., de Zoysa, P., Dorrough, A., Dvoryanchikov, N., Eller, A., Engelmann, J., Euh, H., Fang, X., Fiedler, S., Foster-Gimbel, O., Fülöp, M., Gardarsdottir, R., Gill, C., Glöckner, A., Graf, S., Grigoryan, A., Gritskov, V., Growiec, K., Halama, P., Hartanto, A., Hopthrow, T., Hřebíčková, M., Iliško, D., Imada, H., Kapoor, H., Kawakami, K., Khachatryan, N., Kharchenko, N., Khoury, N., Kiyonari, T., Kohút, M., Linh, L., Leslie, L., Li, Y., Li, N., Li, Z., Liik, K., Maitner, A., Manhique, B., Manley, H., Medhioub, I., Mentser, S., Mohammed, L., Nejat, P., Nipassa, O., Nussinson, R., Onyedire, N., Onyishi, I., Özden, S., Panagiotopoulou, P., Perez-Floriano, L., Persson, M., Pheko, M., Pirttilä-Backman, A., Pogosyan, M., Raver, J., Reyna, C., Rodrigues, R., Romanò, S., Romero, P., Sakki, I., Martin, A., Sherbaji, S., Shimizu, H., Simpson, B., Szabo, E., Takemura, K., Tieffi, H., Teixeira, M., Thanomkul, N., Tiliouine, H., Travaglino, G., Tsirbas, Y., Wan, R., Widodo, S., Zein, R., Zhang, Q., and Lange, L.

Published
2021

48. Perceptions of the appropriate response to norm violation in 57 societies

Author

Eriksson, K., Strimling, P., Gelfand, M., Wu, J., Abernathy, J., Akotia, C., Aldashev, A., Andersson, P., Andrighetto, G., Anum, A., Arikan, G., Aycan, Z., Bagherian, F., Barrera, D., Basnight-Brown, D., Batkeyev, B., Belaus, A., Berezina, E., Björnstjerna, M., Blumen, S., Boski, P., Zeineddine, F., Bovina, I., Huyen, B., Cardenas, J., Čekrlija, Đ., Choi, H., Contreras-Ibáñez, C., Costa-Lopes, R., de Barra, M., de Zoysa, P., Dorrough, A., Dvoryanchikov, N., Eller, A., Engelmann, J., Euh, H., Fang, X., Fiedler, S., Foster-Gimbel, O., Fülöp, M., Gardarsdottir, R., Gill, C., Glöckner, A., Graf, S., Grigoryan, A., Gritskov, V., Growiec, K., Halama, P., Hartanto, A., Hopthrow, T., Hřebíčková, M., Iliško, D., Imada, H., Kapoor, H., Kawakami, K., Khachatryan, N., Kharchenko, N., Khoury, N., Kiyonari, T., Kohút, M., Linh, L., Leslie, L., Li, Y., Li, N., Li, Z., Liik, K., Maitner, A., Manhique, B., Manley, H., Medhioub, I., Mentser, S., Mohammed, L., Nejat, P., Nipassa, O., Nussinson, R., Onyedire, N., Onyishi, I., Özden, S., Panagiotopoulou, P., Perez-Floriano, L., Persson, M., Pheko, M., Pirttilä-Backman, A., Pogosyan, M., Raver, J., Reyna, C., Rodrigues, R., Romanò, S., Romero, P., Sakki, I., Martin, A., Sherbaji, S., Shimizu, H., Simpson, B., Szabo, E., Takemura, K., Tieffi, H., Teixeira, M., Thanomkul, N., Tiliouine, H., Travaglino, G., Tsirbas, Y., Wan, R., Widodo, S., Zein, R., Zhang, Q., and Lange, L.

Published
2021

49. A new species of the genus Stenocercus (Iguania: Tropiduridae) from the Peruvian Pacific coast (Ica region)

Author

Mendoza, A., Ramírez, C., Barrera, D., and Cesar Aguilar Puntriano

Subjects
Squamata, new species, coastal desert, distribution model, taxonomy
Abstract

A new species of the genus Stenocercus is described from the Peruvian coastal desert in the Ica region. The new species is similar in ecology and morphology to Stenocercus modestus, but differs from it in lacking an oblique neck fold, a distinct patch of small scales posterior to the lateral region of the neck, and bright yellow lateral dots on the head and body in males. The new species also has more subdigital lamellae on the fourth toe than S. modestus, and females exhibit a wide dark stripe between the subocular and antehumeral regions, as well as dark reticulations in the gular region. Distribution models of the new species and S. modestus suggest no geographical overlap. In conclusion, morphology and species distribution models strongly imply the new Stenocercus species to be an undescribed lineage and different from all other species of the genus. This new species is the most southerly distributed Stenocercus in the Pacific coastal desert of Peru thus far. We propose the new species be classified as ‘Endangered’ based on its area of occupancy and threat-defined locations.

Published
2021
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50. Author Correction: Perceptions of the appropriate response to norm violation in 57 societies (Nature Communications, (2021), 12, 1, (1481), 10.1038/s41467-021-21602-9)

Author

Eriksson, K. Strimling, P. Gelfand, M. Wu, J. Abernathy, J. Akotia, C.S. Aldashev, A. Andersson, P.A. Andrighetto, G. Anum, A. Arikan, G. Aycan, Z. Bagherian, F. Barrera, D. Basnight-Brown, D. Batkeyev, B. Belaus, A. Berezina, E. Björnstjerna, M. Blumen, S. Boski, P. Bou Zeineddine, F. Bovina, I. Huyen, B.T.T. Cardenas, J.-C. Čekrlija, Đ. Choi, H.-S. Contreras-Ibáñez, C.C. Costa-Lopes, R. de Barra, M. de Zoysa, P. Dorrough, A. Dvoryanchikov, N. Eller, A. Engelmann, J.B. Euh, H. Fang, X. Fiedler, S. Foster-Gimbel, O.A. Fülöp, M. Gardarsdottir, R.B. Gill, C.M.H.D. Glöckner, A. Graf, S. Grigoryan, A. Gritskov, V. Growiec, K. Halama, P. Hartanto, A. Hopthrow, T. Hřebíčková, M. Iliško, D. Imada, H. Kapoor, H. Kawakami, K. Khachatryan, N. Kharchenko, N. Khoury, N. Kiyonari, T. Kohút, M. Linh, L.T. Leslie, L.M. Li, Y. Li, N.P. Li, Z. Liik, K. Maitner, A.T. Manhique, B. Manley, H. Medhioub, I. Mentser, S. Mohammed, L. Nejat, P. Nipassa, O. Nussinson, R. Onyedire, N.G. Onyishi, I.E. Özden, S. Panagiotopoulou, P. Perez-Floriano, L.R. Persson, M.S. Pheko, M. Pirttilä-Backman, A.-M. Pogosyan, M. Raver, J. Reyna, C. Rodrigues, R.B. Romanò, S. Romero, P.P. Sakki, I. San Martin, A. Sherbaji, S. Shimizu, H. Simpson, B. Szabo, E. Takemura, K. Tieffi, H. Mendes Teixeira, M.L. Thanomkul, N. Tiliouine, H. Travaglino, G.A. Tsirbas, Y. Wan, R. Widodo, S. Zein, R. Zhang, Q.-P. Zirganou-Kazolea, L. Van Lange, P.A.M.

Abstract

The original version of this Article contained an error in the author affiliations. Cecilia Reyna was incorrectly associated with ‘Universidad Nacional de Córdoba (UNC). Facultad de Psicología (UNC), Ciudad Universitaria, Bv. de la Reforma esquina, Enfermera Gordillo s/n, Córdoba, Argentina.’ instead of the correct ‘Instituto de Investigaciones Psicológicas (IIPsi), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CABA, República Argentina.’ This has now been corrected in both the PDF and HTML versions of the Article. © The Author(s) 2021

Published
2021

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