Structure-exploiting interior-point solver for high-dimensional entropy-sparsified regression learning

Keyphrases

• Solution Strategies 100%
• Interior-point Solver 100%
• Hessian Matrix 100%
• Dimensional Entropy 100%
• Regression Learning 100%
• Higher-order Derivatives 50%
• High Performance 50%
• Machine Learning Approach 50%
• Robust Solution 50%
• High Performance Computing 50%
• Modular Structure 50%
• Computing Paradigm 50%
• Computing Architecture 50%
• Regression Problem 50%
• High-dimensional Problems 50%
• Effective Structure 50%
• Performance Capability 50%
• Performance Analysis 50%
• Large-scale Problems 50%
• Computing Node 50%
• Solution Time 50%
• Robust Performance 50%
• Second-order Methods 50%
• Nonlinear Regression 50%
• System of Linear Equations 50%
• Message Passing Interface 50%
• Convergence Analysis 50%
• Entropy Method 50%
• Residual Algorithms 50%
• Hybrid Parallelization 50%
• Numerical Robustness 50%
• Distributed Memory Computing 50%
• First-order Information 50%
• Quasi-minimal Residual 50%
• Open Multi-Processing 50%
• Low-rank Update 50%

Computer Science

• Interior Point 100%
• Hessian Matrix 100%
• High-Performance Computing 50%
• Parallelism 50%
• Linear Equation 50%
• Speed-up 50%
• Regression Problem 50%
• Distributed Memory 50%
• Large-Scale Problem 50%
• Computer Architecture 50%
• Message Passing Interface 50%
• Underlying System 50%
• Order Information 50%
• Machine Learning Approach 50%
• Multiprocessing 50%
• Robust Solution 50%
• computing paradigm 50%
• Dimensional Problem 50%
• Nonlinear Regression 50%
• Performance Analysis 50%