Deepström: ´ Emulsion de noyaux et d'apprentissage profond

International audienceLes modèles à base de méthodes à noyaux et d'apprentissage profond ont essentiellement été étudiés séparemment jusqu'à aujourd'hui. Des travaux récents se sont focalisés sur la combinaison de ces deux approches afin de tirer parti du meilleur de chacune d'elles. Dans cette optique, nous introduisons une nouvelle architecture de réseaux de neurones qui bénéficie du faible coût en espace et en temps de l'approximation de Nyström. Nous montrons que cette architecture atteint une performance du niveau de l'état de l'art sur la classification d'images des jeux de données MNIST et CIFAR10 tout en ne nécessitant qu'un nombre réduit de paramètres

Immunotherapy with MVA-BN®-HER2 induces HER-2-specific Th1 immunity and alters the intratumoral balance of effector and regulatory T cells

MVA-BN®-HER2 is a new candidate immunotherapy designed for the treatment of HER-2-positive breast cancer. Here, we demonstrate that a single treatment with MVA-BN®-HER2 exerts potent anti-tumor efficacy in a murine model of experimental pulmonary metastasis. This anti-tumor efficacy occurred despite a strong tumor-mediated immunosuppressive environment characterized by a high frequency of regulatory T cells (Treg) in the lungs of tumor-bearing mice. Immunogenicity studies showed that treatment with MVA-BN®-HER2 induced strongly Th1-dominated HER-2-specific antibody and T-cell responses. MVA-BN®-HER2-induced anti-tumor activity was characterized by an increased infiltration of lungs with highly activated, HER-2-specific, CD8+CD11c+ T cells accompanied by a decrease in the frequency of Treg cells in the lung, resulting in a significantly increased ratio of effector T cells to Treg cells. In contrast, administration of HER2 protein formulated in Complete Freund’s Adjuvant (CFA) induced a strongly Th2-biased immune response to HER-2. However, this did not lead to significant infiltration of the tumor-bearing lungs by CD8+ T cells or the decrease in the frequency of Treg cells nor did it result in anti-tumor efficacy. In vivo depletion of CD8+ cells confirmed that CD8 T cells were required for the anti-tumor activity of MVA-BN®-HER2. Furthermore, depletion of CD4+ or CD25+ cells demonstrated that tumor-induced Treg cells promoted tumor growth and that CD4 effector cells also contribute to MVA-BN®-HER2-mediated anti-tumor efficacy. Taken together, our data demonstrate that treatment with MVA-BN®-HER2 controls tumor growth through mechanisms including the induction of Th1-biased HER-2-specific immune responses and the control of tumor-mediated immunosuppression

Deep Networks with Adaptive Nyström Approximation

International audienceRecent work has focused on combining kernel methods and deep learning to exploit the best of the two approaches. Here, we introduce a new architecture of neural networks in which we replace the top dense layers of standard convolutional architectures with an approximation of a kernel function by relying on the Nyström approximation. Our approach is easy and highly flexible. It is compatible with any kernel function and it allows exploiting multiple kernels. We show that our architecture has the same performance than standard architecture on datasets like SVHN and CIFAR100. One benefit of the method lies in its limited number of learnable parameters which makes it particularly suited for small training set sizes, e.g. from 5 to 20 samples per class

Deepström: ´ Emulsion de noyaux et d'apprentissage profond

International audienceLes modèles à base de méthodes à noyaux et d'apprentissage profond ont essentiellement été étudiés séparemment jusqu'à aujourd'hui. Des travaux récents se sont focalisés sur la combinaison de ces deux approches afin de tirer parti du meilleur de chacune d'elles. Dans cette optique, nous introduisons une nouvelle architecture de réseaux de neurones qui bénéficie du faible coût en espace et en temps de l'approximation de Nyström. Nous montrons que cette architecture atteint une performance du niveau de l'état de l'art sur la classification d'images des jeux de données MNIST et CIFAR10 tout en ne nécessitant qu'un nombre réduit de paramètres

PSM-nets: Compressing Neural Networks with Product of Sparse Matrices

International audienceOver-parameterization of neural networks is a well known issue that comes along with their great performance. Among the many approaches proposed to tackle this problem, low-rank tensor decompositions are largely investigated to compress deep neural networks. Such techniques rely on a low-rank assumption of the layer weight tensors that does not always hold in practice. Following this observation, this paper studies sparsity inducing techniques to build new sparse matrix product layers for high-rate neural networks compression. Specifically, we explore recent advances in sparse optimization to replace each layer's weight matrix, either convolutional or fully connected, by a product of sparse matrices. Our experiments validate that our approach provides a better compression-accuracy trade-off than most popular low-rank-based compression techniques

Cationic Lipid/DNA Complex-Adjuvanted Influenza A Virus Vaccination Induces Robust Cross-Protective Immunity▿

Influenza A virus is a negative-strand segmented RNA virus in which antigenically distinct viral subtypes are defined by the hemagglutinin (HA) and neuraminidase (NA) major viral surface proteins. An ideal inactivated vaccine for influenza A virus would induce not only highly robust strain-specific humoral and T-cell immune responses but also cross-protective immunity in which an immune response to antigens from a particular viral subtype (e.g., H3N2) would protect against other viral subtypes (e.g., H1N1). Cross-protective immunity would help limit outbreaks from newly emerging antigenically novel strains. Here, we show in mice that the addition of cationic lipid/noncoding DNA complexes (CLDC) as adjuvant to whole inactivated influenza A virus vaccine induces significantly more robust adaptive immune responses both in quantity and quality than aluminum hydroxide (alum), which is currently the most widely used adjuvant in clinical human vaccination. CLDC-adjuvanted vaccine induced higher total influenza virus-specific IgG, particularly for the IgG2a/c subclass. Higher levels of multicytokine-producing influenza virus-specific CD4 and CD8 T cells were induced by CLDC-adjuvanted vaccine than with alum-adjuvanted vaccine. Importantly, CLDC-adjuvanted vaccine provided significant cross-protection from either a sublethal or lethal influenza A viral challenge with a different subtype than that used for vaccination. This superior cross-protection afforded by the CLDC adjuvant required CD8 T-cell recognition of viral peptides presented by classical major histocompatibility complex class I proteins. Together, these results suggest that CLDC has particular promise for vaccine strategies in which T cells play an important role and may offer new opportunities for more effective control of human influenza epidemics and pandemics by inactivated influenza virus vaccine