搜索结果: 1-15 共查到“数学 algorithms”相关记录101条 . 查询时间(0.14 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:On strongly quasiconvex functions: existence results and proximal point algorithms
强准孔函数 存在结果 近端点算法
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2023/5/4
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Primal Dual Alternating Proximal Gradient Algorithms for Nonsmooth Nonconvex Minimax Problems with Coupled Linear Constraints
耦合 线性约束 非光滑 非凸极小问题 基本对偶交替 近端梯度算法
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2023/4/14
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Submodular Functions: Extensions, Distributions, and Algorithms
子模块函数 扩展 分布 算法
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2023/5/8
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Quantum algorithms for nonlinear partial differential equations
非线性 偏微分方程 量子算法
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2023/5/16
2018新架构和算法研讨会(Workshop on New Architectures and Algorithms)
2018 新架构和算法 研讨会
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2017/12/20
Over the last decade, the computing needs of modern enterprise and industry have expanded to include machine intelligence, cloud computing, and HPC. In the next decade, these communities will rely on...
2018年ACM-SIAM离散算法研讨会(ACM-SIAM Symposium on Discrete Algorithms)
2018年 ACM-SIAM 离散算法 研讨会
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2017/12/20
This symposium focuses on research topics related to efficient algorithms and data structures for discrete problems. In addition to the design of such methods and structures, the scope also includes t...
2018年SIAM简单算法研讨会(Symposium on Simplicity in Algorithms)
2018年 SIAM 简单算法 研讨会
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2017/12/20
The First Symposium on Simplicity in Algorithms will be co-located with The 29th ACM-SIAM Symposium on Discrete Algorithms (SODA 2018) in New Orleans, LA, USA, January 7–10, 2018.Symposium on Simplic...
三亚国际数学论坛:High Performance Numerical Algorithms and Applications
三亚国际数学论坛 High Performance Numerical Algorithms and Applications
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2017/11/24
Scalable parallel algorithms for partial differential equations (PDEs) play a key role in computational science and engineering. As the number of processor cores in today's supercomputers grows rapidl...
Fast Algorithms for Signal Reconstruction without Phase
Frames mutually unbiased bases equiangular frames projective 2-designs discrete chirps
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2015/9/29
We derive fast algorithms for doing signal reconstruction without phase. This type of problem is important insignal processing, especially speech recognition technology, and has relevance for state to...
Algorithms for Representation Theory of Real Reductive Groups
Representation Theory Real Reductive Groups
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2015/9/28
The irreducible admissible representations of a real reductive group such as GL(n, R) have been classified by work of Langlands, Knapp, Zuckerman and Vogan. This classification is somewhat involved an...
Universality in Polytope Phase Transitions and Message Passing Algorithms
Nonlinear mapping symmetric random matrix spin glass theory approximate messaging algorithm
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2015/8/21
We consider a class of nonlinear mappings FA;N in RN indexed by symmetric random matrices A 2 RNN with independent entries. Within spin glass theory, special cases of these mappings correspond to ite...
NEW MULTICATEGORY BOOSTING ALGORITHMS BASED ON MULTICATEGORY FISHER-CONSISTENT LOSSES
MULTICATEGORY BOOSTING ALGORITHMS MULTICATEGORY FISHER-CONSISTENT LOSSES
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2015/8/21
Fisher-consistent loss functions play a fundamental role in the construction of successful binary margin-based classifiers. In this paper we establish the Fisher-consistency condition for multicategor...
BOOSTING ALGORITHMS:REGULARIZATION,PREDICTION AND MODEL FITTING
Generalized linear models Generalized additive models Gradient boosting Survival analysis Variable selection Software
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2015/8/21
We present a statistical perspective on boosting. Special emphasis is given to estimating potentially complex parametric or nonparametric models, including generalized linear and additive models as we...
Comment:Boosting Algorithms:Regularization,Prediction and Model Fitting
Boosting Algorithms Regularization Prediction Model Fitting
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2015/8/21
We congratulate the authors (hereafter BH) for an interesting take on the boosting technology, and for developing a modular computational environment in R for exploring their models. Their use of low-...
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
collaborative filtering nuclear norm spectral regularization netflix prize large scale convex optimization
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2015/8/21
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and...