non-convex-optimization

Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.

optimization constraints constrained-optimization constraint-programming robotics-control constraint-based-modeling safety-critical safety-critical-systems differentiable-programming non-convex-optimization safe-reinforcement-learning constrained-learning safe-control constrained-reinforcement-learning safe-planning safety-critical-learning

UpdatedJul 23, 2022
Python

hiroyuki-kasai /RSOpt

Star66

Riemannian stochastic optimization algorithms: Version 1.0.3

machine-learning big-data optimization machine-learning-algorithms constrained-optimization sgd manifold nonlinear-optimization optimization-algorithms large-scale-learning online-learning stochastic-optimizers variance-reduction stochastic-gradient-descent nonlinear-optimization-algorithms stochastic-optimization riemannian-manifold riemannian-optimization non-convex-optimization

UpdatedJan 5, 2023
MATLAB

mynkpl1998 /Deep-Learning-Optimization-Algorithms

Star60

Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.

deep-learning python3 pytorch adadelta optimization-algorithms convex-optimization stochastic-gradient-descent saddlepoint-approximation adamoptimizer non-convex-optimization

UpdatedJun 21, 2018
Jupyter Notebook

vkumar-ucd /IRS_MIMO_UnderlaySpectrumSharing

Star25

Simulation code for "Achievable Rate Maximization for Underlay Spectrum Sharing MIMO System with Intelligent Reflecting Surface," by V. Kumar, M. F. Flanagan, R. Zhang, and L. -N. Tran, IEEE Wireless Communications Letters, 2022, doi: 10.1109/LWC.2022.3180988.

signal-processing convex-optimization wireless-communication mimo cognitive-radio non-convex-optimization alternating-optimization spectrum-sharing intelligent-reflecting-surfaces gradient-projection penalty-methods

UpdatedNov 1, 2023
Python

hongyanz /multibranch

Star21

Codes for the paper "Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex"

machine-learning deep-learning non-convex-optimization

UpdatedJul 25, 2020
Python

KonstantinRiedl /CBOGlobalConvergenceAnalysis

Star20

Numerical illustration of a novel analysis framework for consensus-based optimization (CBO) and numerical experiments demonstrating the practicability of the method

machine-learning optimization illustration mnist classification global-optimization numerical-analysis metaheuristics high-dimensional non-convex-optimization derivative-free-optimization consensus-optimization

UpdatedNov 13, 2023
MATLAB

vkumar-ucd /EffectiveSecrecyRate

Star18

Simulation code for "On the Secrecy Rate under Statistical QoS Provisioning for RIS-assisted MISO Wiretap Channel," by V. Kumar, M. F. Flanagan, D. W. Kwan Ng, and L. -N. Tran, IEEE Global Communications Conference (GLOBECOM), 2021, pp. 1-6, doi: 10.1109/GLOBECOM46510.2021.9685957.

signal-processing convex-optimization wireless-communication non-convex-optimization physical-layer-security alternating-optimization intelligent-reflecting-surfaces reconfigurable-intelligent-surfaces secrecy-capacity

UpdatedAug 29, 2022
Python

fouratifares /ECP

Star16

Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants

machine-learning optimization optimizer global-optimization black-box-optimization nonlinear-optimization optimization-algorithms global-optimization-algorithms non-linear-optimization non-convex-optimization lipschitz-functions zeroth-order-optimization zero-order-methods lipschitz-bandit

UpdatedNov 30, 2025
Jupyter Notebook

matthieumeo /pyoneer

Star10

Pyoneer is a Python 3 package for the continuous recovery of non-bandlimited periodic signals with finite rates of innovation (e.g. Dirac streams) from generalised measurements.

signal-processing python3 finite-rate-of-innovation periodic-signals non-uniform-sampling sampling-theory non-convex-optimization denoising-algorithm proximal-gradient-descent cpgd