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Showing 12 open source projects for "problem a"
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MCM-ICM
Mathematical Contest resources
MCM-ICM is a curated archive of Outstanding Winner (“O-奖/特等奖”) solution papers from the Mathematical Contest in Modeling and the Interdisciplinary Contest in Modeling, spanning the early 2000s through recent years. The repository is organized by year, with per-year folders that collect the top-ranked reports and, in later years, additional materials such as problem statements or problem notes when available. It has evolved from a single-maintainer project into a collaborative effort, with different contributors stewarding successive year ranges so the collection stays current. The contents skew toward MATLAB and LaTeX, reflecting the tools most winning teams use to build models and typeset their reports; you’ll typically see complete write-ups alongside code that implements optimization, simulation, statistical analysis, or other modeling pipelines. -
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A Matlab toolkit for all aspects of EEG/ERP analysis, especially PCA. If you run into a problem, please send me a note and I'll fix it. The tutorial pdf is in the documentation folder and the tutorial data can be downloaded from a link provided by the pdf. The tutorial file has full install instructions. For all platforms supported by Matlab.
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GRAMPC
A gradient-based augmented Lagrangian framework for embedded NMPC
GRAMPC is a nonlinear MPC framework that is suitable for dynamical systems with sampling times in the (sub)millisecond range and that allows for an efficient implementation on embedded hardware. The algorithm is based on an augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. GRAMPC is implemented in plain C with an additional interface to C++ and MATLAB/Simulink. The basic structure and usage of GRAMPC are described in the documentation that comes along with the source files. More details about the algorithm and its performance can be found in the corresponding article published in Optimization and Engeneering. ... -
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Continuation Core and Toolboxes (COCO)
Toolboxes for parameter continuation and bifurcation analysis.
Development platform and toolboxes for parameter continuation, e.g., bifurcation analysis of dynamical systems and constrained design optimization. This material is based upon work partially supported by the National Science Foundation under Grant No. 1016467 and the Danish research council (FTP) under the project number 0602-00753B. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the... -
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Math Model
Code, resources, and templates for mathematical modeling
...It includes LaTeX templates for writing solutions, records of past contest problems and winning solutions, algorithm implementations in MATLAB / M scripts for optimization, intelligent algorithms, numerical methods, and model frameworks. In effect, it is a curated library of modeling code, papers, templates, and algorithm summaries tailored to competition preparation. Historical problem and solution archives from many contests. Summary of contest evaluation criteria and heuristics. -
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Mathematics
Accumulation of mathematical knowledge, matrix numerical optimization
...The repository organizes material across pure and applied mathematics, including calculus, linear algebra, probability, statistics, and optimization. It also extends into computational and algorithmic applications of mathematics, making it a useful reference for both academic study and practical problem-solving. The goal is to provide learners, researchers, and developers with a consolidated source of foundational and advanced mathematical concepts. By gathering a diverse set of topics into one repository, it supports continuous learning and interdisciplinary exploration. Its open source nature allows for community contributions and adaptation to different educational or research needs. -
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OpenOCL Matlab
Optimal control, trajectory optimization, model-predictive control.
The Open Optimal Control Library is a software framework in Matlab/Octave for modeling optimal control problem. It uses automatic differentiation and fast non-linear programming solvers. It implements direct methods. In the backend it uses CasADi and ipopt. -
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SparesPOP is a MATLAB implementation of a sparse semidefinite programming (SDP) relaxation method proposed for polynomial optimization problems (POPs). Please send a message to kojima-spop@is.titech.ac.jp if you have any question and/or request. We also release SparsePOPC++ and SparsePOPC++-windows. Both implementations are SparsePOP which does not use MATLAB, but only C++. In particular, SparsePOPC++-windows contains a binary file which works on Windows, and does not require to compile.
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MetaMIS
Metagenomic Microbial Interaction Simulator
...MetaMIS provides a user-friendly interactive stand-alone graphical interface for scientists without programming skills to investigate the interactions among microorganisms. 2017.03.09 MetaMIS_v1.02: - Create an option to export consensus table. - Decimal time is allowed. 2016.12.16 MetaMIS_v1.01: - fix the memory-out problem for larger abundance table (>500 OTUs). - add three items to constrain the total number of running interaction networks 2016.11.17 MetaMIS_v1 -
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LRPR
Low Rank Page Rank: A matlab project in sparse matrix computation
The problem of Pagerank is a simple one to state: Given a collection of websites, how do we rank them? The primary way of formulating this utilizes a transition matrix which relates how web pages interact with each other. We investigate what the effect of a low rank approximation for the transition matrix has on the power method and an inner-outer iteration for solving the Pagerank problem. -
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Functional Mechanism
Regression Analysis under Differential Privacy
Functional Mechanism is a differentially private method designed for a large class of optimization-based analyses. The main idea is to enforce epsilon-differential privacy by perturbing the objective function of the optimization problem, rather than its results. Please cite the following paper if you choose to use this code: J. Zhang, Z. Zhang, X. Xiao, Y. Yang, and M. Winslett. Functional Mechanism: Regression Analysis under Differential Privacy. PVLDB 5(11):1364-1375, 2012. -
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DCTV
DUAL CONSTRAINED TV-BASED REGULARIZATION ON GRAPHS
...In this work, we extend the TV dual framework that includes Chambolle's and Gilboa-Osher's projection algorithms for TV minimization. We use a flexible graph data representation that allows us to generalize the constraint on the projection variable. We show how this new formulation of the TV problem may be solved by means of fast parallel proximal algorithms. On denoising and deblurring examples, the proposed approach is shown not only to perform better than recent TV-based approaches, but also to perform well on arbitrary graphs instead of regular grids. The proposed method consequently applies to a variety of other inverse problems including image fusion and mesh filtering.
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