Adaptive Neural Compilation

This paper proposes an adaptive neural-compilation framework to address the problem of efficient program learning. Traditional code optimisation strategies used in compilers are based on applying pre-specified set of transformations that make the code faster to execute without changing its semantics. In contrast, our work involves adapting programs to make them more efficient while considering correctness only on a target input distribution. Our approach is inspired by the recent works on differentiable representations of programs. We show that it is possible to compile programs written in a low-level language to a differentiable representation. We also show how programs in this representation can be optimised to make them efficient on a target distribution of inputs. Experimental results demonstrate that our approach enables learning specifically-tuned algorithms for given data distributions with a high success rate.Comment: Submitted to NIPS 2016, code and supplementary materials will be available on author's pag

Efficient Linear Programming for Dense CRFs

The fully connected conditional random field (CRF) with Gaussian pairwise potentials has proven popular and effective for multi-class semantic segmentation. While the energy of a dense CRF can be minimized accurately using a linear programming (LP) relaxation, the state-of-the-art algorithm is too slow to be useful in practice. To alleviate this deficiency, we introduce an efficient LP minimization algorithm for dense CRFs. To this end, we develop a proximal minimization framework, where the dual of each proximal problem is optimized via block coordinate descent. We show that each block of variables can be efficiently optimized. Specifically, for one block, the problem decomposes into significantly smaller subproblems, each of which is defined over a single pixel. For the other block, the problem is optimized via conditional gradient descent. This has two advantages: 1) the conditional gradient can be computed in a time linear in the number of pixels and labels; and 2) the optimal step size can be computed analytically. Our experiments on standard datasets provide compelling evidence that our approach outperforms all existing baselines including the previous LP based approach for dense CRFs.Comment: 24 pages, 10 figures and 4 table

Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials

Dense conditional random fields (CRFs) have become a popular framework for modelling several problems in computer vision such as stereo correspondence and multi-class semantic segmentation. By modelling long-range interactions, dense CRFs provide a labelling that captures finer detail than their sparse counterparts. Currently, the state-of-the-art algorithm performs mean-field inference using a filter-based method but fails to provide a strong theoretical guarantee on the quality of the solution. A question naturally arises as to whether it is possible to obtain a maximum a posteriori (MAP) estimate of a dense CRF using a principled method. Within this paper, we show that this is indeed possible. We will show that, by using a filter-based method, continuous relaxations of the MAP problem can be optimised efficiently using state-of-the-art algorithms. Specifically, we will solve a quadratic programming (QP) relaxation using the Frank-Wolfe algorithm and a linear programming (LP) relaxation by developing a proximal minimisation framework. By exploiting labelling consistency in the higher-order potentials and utilising the filter-based method, we are able to formulate the above algorithms such that each iteration has a complexity linear in the number of classes and random variables. The presented algorithms can be applied to any labelling problem using a dense CRF with sparse higher-order potentials. In this paper, we use semantic segmentation as an example application as it demonstrates the ability of the algorithm to scale to dense CRFs with large dimensions. We perform experiments on the Pascal dataset to indicate that the presented algorithms are able to attain lower energies than the mean-field inference method

Mechanical Properties and Oxidation Behaviour of Electroconductive Ceramic Composites

International audienceDense electroconductive ceramic-ceramic composites silicon carbide-hafnium diboride (SiC-HfB2) and silicon carbide-hafnium carbide (SiC-HfC) were obtained by Hot Pressing (HP). In view of the results, the high performance composite grade SiC-HfB2 has also been elaborated by Hot Isostatic Pressing (HIP). For 25 mol % HfC or HfB2 content, the resistivity was low enough to allow electrodischarged machining (EDM). The mechanical and thermal properties as well as the wear and oxidation behaviours were evaluated and compared. The electroconductive boride composite (75-25 mol% SiC-HfB2) exhibits high mechanical properties. The benefit of the diboride phase's presence is also noticed in fluent oxygen, up to 1450°C. The SiC-HfB2 composite is as resistant as silicon carbide. This behaviour may be related to the formation of a borosilicate based oxide layer containing hafnium phases, which plays the role of a coating and which limits the B2O3 evaporation

Colloquium: Mechanical formalisms for tissue dynamics

The understanding of morphogenesis in living organisms has been renewed by tremendous progressin experimental techniques that provide access to cell-scale, quantitative information both on theshapes of cells within tissues and on the genes being expressed. This information suggests that ourunderstanding of the respective contributions of gene expression and mechanics, and of their crucialentanglement, will soon leap forward. Biomechanics increasingly benefits from models, which assistthe design and interpretation of experiments, point out the main ingredients and assumptions, andultimately lead to predictions. The newly accessible local information thus calls for a reflectionon how to select suitable classes of mechanical models. We review both mechanical ingredientssuggested by the current knowledge of tissue behaviour, and modelling methods that can helpgenerate a rheological diagram or a constitutive equation. We distinguish cell scale ("intra-cell")and tissue scale ("inter-cell") contributions. We recall the mathematical framework developpedfor continuum materials and explain how to transform a constitutive equation into a set of partialdifferential equations amenable to numerical resolution. We show that when plastic behaviour isrelevant, the dissipation function formalism appears appropriate to generate constitutive equations;its variational nature facilitates numerical implementation, and we discuss adaptations needed in thecase of large deformations. The present article gathers theoretical methods that can readily enhancethe significance of the data to be extracted from recent or future high throughput biomechanicalexperiments.Comment: 33 pages, 20 figures. This version (26 Sept. 2015) contains a few corrections to the published version, all in Appendix D.2 devoted to large deformation

Oxidation behaviour of a hot isostatically pressed silicon nitride material

The oxidation behaviour of a dense silicon nitride material containing the minimum amount of additives was studied. A silicon nitride powder was hot isostatically pressed in the presence of 0.5 wt% Y2O3 and 0.025 wt%Al2O3. The dense material obtained was oxidized for 24 hours, in an oxygen atmosphere within the temperature range 1475-1650°C. The high oxidation resistance of this material may be related to the low amount of sintering aid initially introduced and consequently to the composition of the grain boundary phase. According to the temperature, the apparent activation energies for the oxidation processes, ranged from 355 to 680 kJ/mol

DEFECT DETECTION IN ENGINEERING CERAMICS USING DIFFERENT NON DESTRUCTIVE TESTING TECHNIQUES

L'emploi des céramiques pour applications mécaniques à haute température et longue durée de vie nécessite des moyens de contrôle non destructif très performants. A cause des caractéristiques particulières de ces matériaux et de la faible taille des défauts recherchés, les techniques mises en oeuvre font l'objet d'un choix rigoureux. Leur application au contrôle industriel est discutée.The use of ceramics for high temperature and long lifetime applications require very sensitive non-destructive testing techniques. Due to the particular characteristics of these materials, and to the very small size of the flaws to be detected, they must be selected very strictly. Their application to industrial control is discussed