Lipschitz constant estimation for 1D convolutional neural networks

In this work, we propose a dissipativity-based method for Lipschitz constant estimation of 1D convolutional neural networks (CNNs). In particular, we analyze the dissipativity properties of convolutional, pooling, and fully connected layers making use of incremental quadratic constraints for nonlinear activation functions and pooling operations. The Lipschitz constant of the concatenation of these mappings is then estimated by solving a semidefinite program which we derive from dissipativity theory. To make our method as efficient as possible, we take the structure of convolutional layers into account realizing these finite impulse response filters as causal dynamical systems in state space and carrying out the dissipativity analysis for the state space realizations. The examples we provide show that our Lipschitz bounds are advantageous in terms of accuracy and scalability

Neural network training under semidefinite constraints

This paper is concerned with the training of neural networks (NNs) under semidefinite constraints, which allows for NN training with robustness and stability guarantees. In particular, we focus on Lipschitz bounds for NNs. Exploiting the banded structure of the underlying matrix constraint, we set up an efficient and scalable training scheme for NN training problems of this kind based on interior point methods. Our implementation allows to enforce Lipschitz constraints in the training of large-scale deep NNs such as Wasserstein generative adversarial networks (WGANs) via semidefinite constraints. In numerical examples, we show the superiority of our method and its applicability to WGAN training.Comment: to be published in 61st IEEE Conference on Decision and Contro

Convolutional Neural Networks as 2-D systems

This paper introduces a novel representation of convolutional Neural Networks (CNNs) in terms of 2-D dynamical systems. To this end, the usual description of convolutional layers with convolution kernels, i.e., the impulse responses of linear filters, is realized in state space as a linear time-invariant 2-D system. The overall convolutional Neural Network composed of convolutional layers and nonlinear activation functions is then viewed as a 2-D version of a Lur'e system, i.e., a linear dynamical system interconnected with static nonlinear components. One benefit of this 2-D Lur'e system perspective on CNNs is that we can use robust control theory much more efficiently for Lipschitz constant estimation than previously possible

Ash pollen immunoproteomics: Identification, immunologic characterization, and sequencing of 6 new allergens

Immunoproteomics, IgE-inhibition assays and cDNA-cloning reveals that ash and olive allergenic protein profiles are mostly equivalent, thus explaining their high cross reactivity. Our data suggest simplifying diagnosis of patients by using indistinctly ash or olive pollen

Cardiac Actions of a Small Molecule Inhibitor Targeting GATA4–NKX2-5 Interaction

Transcription factors are fundamental regulators of gene transcription, and many diseases, such as heart diseases, are associated with deregulation of transcriptional networks. In the adult heart, zinc-finger transcription factor GATA4 is a critical regulator of cardiac repair and remodelling. Previous studies also suggest that NKX2-5 plays function role as a cofactor of GATA4. We have recently reported the identification of small molecules that either inhibit or enhance the GATA4–NKX2-5 transcriptional synergy. Here, we examined the cardiac actions of a potent inhibitor (3i-1000) of GATA4–NKX2-5 interaction in experimental models of myocardial ischemic injury and pressure overload. In mice after myocardial infarction, 3i-1000 significantly improved left ventricular ejection fraction and fractional shortening, and attenuated myocardial structural changes. The compound also improved cardiac function in an experimental model of angiotensin II -mediated hypertension in rats. Furthermore, the up-regulation of cardiac gene expression induced by myocardial infarction and ischemia reduced with treatment of 3i-1000 or when micro- and nanoparticles loaded with 3i-1000 were injected intramyocardially or intravenously, respectively. The compound inhibited stretch- and phenylephrine-induced hypertrophic response in neonatal rat cardiomyocytes. These results indicate significant potential for small molecules targeting GATA4–NKX2-5 interaction to promote myocardial repair after myocardial infarction and other cardiac injuries.Peer reviewe

SF3B1 facilitates HIF1-signaling and promotes malignancy in pancreatic cancer

Mutations in the splicing factor SF3B1 are frequently occurring in various cancers and drive tumor progression through the activation of cryptic splice sites in multiple genes. Recent studies also demonstrate a positive correlation between the expression levels of wild-type SF3B1 and tumor malignancy. Here, we demonstrate that SF3B1 is a hypoxia-inducible factor (HIF)-1 target gene that positively regulates HIF1 pathway activity. By physically interacting with HIF1α, SF3B1 facilitates binding of the HIF1 complex to hypoxia response elements (HREs) to activate target gene expression. To further validate the relevance of this mechanism for tumor progression, we show that a reduction in SF3B1 levels via monoallelic deletion of Sf3b1 impedes tumor formation and progression via impaired HIF signaling in a mouse model for pancreatic cancer. Our work uncovers an essential role of SF3B1 in HIF1 signaling, thereby providing a potential explanation for the link between high SF3B1 expression and aggressiveness of solid tumors

Integración de datos económico-financieros y de personal al datawarehouse-UNC como soporte de gestión y toma de decisiones

El propósito de este proyecto consiste en profundizar el estado de implementación de la herramienta 03 y consolidar su funcionamiento (explotar su potencial: publicar reportes web y generar indicadores)Fil: Montenegro, Miguel. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Presupuesto, Argentina.Fil: Zoccari, Gabriel. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Presupuesto, Argentina.Fil: Cravero, Patricia. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Personal, Argentina.Fil: Aveta, Amelia. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Contabilidad y Finanzas, Argentina.Fil: Rizzo Centeno, María Alejandra. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Presupuesto, Argentina.Fil: Durand Pauli, Graciela. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Presupuesto, Argentina.Fil: Rodríguez de Marco, Diego. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Presupuesto, Argentina.Fil: Novillo, Estela. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Personal, Argentina.Fil: Fontanelas, María Elena. Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Personal, Argentina.Fil: Montoya, Juan.Universidad Nacional de Córdoba. Secretaría de Planificación y Gestión Institucional, Dirección General de Tecnologías Informáticas, Argentina.Fil: Domina Cecilia. SIU, Argentina