Showing 4 open source projects for "search engine optimization"

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  • 1
    Bullet Physics SDK

    Bullet Physics SDK

    Real-time collision detection and multi-physics simulation for VR

    ...It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained using Deep Reinforcement Learning, or using Gradient based optimization (for example LFBGS). In addition, the simulator can be entirely run on CUDA for fast rollouts, in combination with Augmented Random Search. This allows for 1 million simulation steps per second. It is highly recommended to use PyBullet Python bindings for improved support for robotics, reinforcement learning and VR. Use pip install pybullet and checkout the PyBullet Quickstart Guide.
    Downloads: 6 This Week
    Last Update:
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  • 2
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    ...Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
    Downloads: 0 This Week
    Last Update:
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  • 3

    Genetic Algorithms Engine - Blackjack

    A genetic algortihm engine that evolves blackjack basic strategy.

    ...The code was written in C++, using MS Visual Studio 6.0 and MS Visual Source Safe 6.0. The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. To use the genetic algorithm engine to search for a different problem's solution, one needs to program a fitness function, the project settings, and a few virtual functions.
    Downloads: 0 This Week
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  • 4

    Large Scale Optimization Templates

    C++ templates with generic nonlinear optimization algorithms

    Highly tunable, simple to use collection of the templates, containing a set of classes for solving unconstrained large scale nonlinear optimization problems. Currently it contains: -- Limited Memory Quasi Newton (L-BFSG) -- BFSG -- Conjugate Gradient -- Gradient Descent -- Wolf condition Line Search -- Backtracking Line Search -- Exact Golden Search -- Golden Search with Wolf condition We also distribute a set of tests with the library.
    Downloads: 0 This Week
    Last Update:
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