Results 121 to 130 of about 350,996 (311)

Catenary Support Vector Machines [PDF]

, 2008
Many problems require making sequential decisions. For these problems, the benefit of acquiring further information must be weighed against the costs. In this paper, we describe the catenary support vector machine(catSVM), a margin-based method to solve sequential stopping problems.
Kin Fai Kan, Christian R. Shelton
openaire   +1 more source

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

Advanced Engineering Materials, EarlyView.
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang, Aparajita Pramanik, Sandipan Sen, Shubhashis Dixit, Marcel Muench, R. J. Vikram, Daniel Schliephake, Yolita M. Eggeler, Ankur Chauhan, Martin Heilmaier, Alexander Kauffmann   +10 more
wiley   +1 more source

Compressed Support Vector Machines

CoRR, 2015
Support vector machines (SVM) can classify data sets along highly non-linear decision boundaries because of the kernel-trick. This expressiveness comes at a price: During test-time, the SVM classifier needs to compute the kernel inner-product between a test sample and all support vectors.
Zhixiang Eddie Xu, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger   +3 more
openaire   +2 more sources

Creep Properties and Deformation Mechanism of Additively Manufactured NiAl‐CrMo Composites

Advanced Engineering Materials, EarlyView.
Additively manufactured NiAl‐CrMo composites contain numerous interfaces and cell boundaries that control their creep response. At 700°C under high applied stress, creep is dominated by dislocation‐controlled power‐law mechanisms. At 800°C–900°C and lower stresses, creep is primarily diffusion‐controlled along cell boundaries.
Jan Vollhüter, Andreas Bezold, Johan Westraadt, Katharina Fiegl, Subham Chattoraj, Benjamin Wahlmann, Carolin Körner, Michael Mills, Mathias Göken, Steffen Neumeier   +9 more
wiley   +1 more source

Support vector machines and generalisation in HEP

Journal of Physics: Conference Series, 2016
We review the concept of support vector machines (SVMs) and discuss examples of their use. One of the benefits of SVM algorithms, compared with neural networks and decision trees is that they can be less susceptible to over fitting than those other algorithms are to over training. This issue is related to the generalisation of a multivariate algorithm (
Agni Bethani, Adrian J. Bevan, Jon Hays, Tom J. Stevenson   +3 more
openaire   +3 more sources

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

The Study of Information Security Risk Assessment Based on Support Vector Machine

MATEC Web of Conferences, 2018
This paper establishes an information security evaluation model based on support vector machine by analyzing the factors affecting information security risk assessment.
Xie Haiyan, Wang Ying, Zhang Xianghong
doaj   +1 more source

survival-support-vector-machine: Version 1.0

, 2015
<p>This version contains the code and data that was used to produce the results of the ECML PKDD 2015 paper "Fast Training of Support Vector Machines for Survival Analysis" by Pölsterl et al.</p ...
Sebastian Pölsterl
core   +1 more source

In Situ Micromechanical Study of Bimodal γ′–γ″ Precipitate Assemblies in Ni–Cr–Al–Nb Superalloy

Advanced Engineering Materials, EarlyView.
A Ni–Cr–Al–Nb superalloy with a bimodal γ′–γ″ precipitate distribution is developed. Composite precipitate assemblies form through heterogeneous nucleation, effectively impeding dislocation motion. Micropillar compression reveals high strength at room and elevated temperatures, governed by precipitate shearing, with coupled faulting mechanisms ...
Ujjval Bansal, Tae‐Hyeok Kang, Pyuck‐Pa Choi, Subin Lee, Christoph Kirchlechner   +4 more
wiley   +1 more source

Semismooth Support Vector Machines

, 2000
The linear support vector machine can be posed as a quadratic pro- gram in a variety of ways. In this paper, we look at a formulation using the two-norm for the misclassi cation error that leads to a positive de - nite quadratic program with a single ...
Ferris, Michael, Munson, Todd
core