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ENTITY convex optimization

convex optimization

PulseAugur coverage of convex optimization — every cluster mentioning convex optimization across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_174155 ·

    New research proposes dynamic batch size schedules for LLM training

    Researchers have developed a new method for training deep learning models by dynamically adjusting the batch size alongside the learning rate. This approach, grounded in convex optimization, provides a closed-form optim…

  2. RESEARCH · CL_141226 ·

    New algorithms tackle contextual combinatorial semi-bandit problems with improved efficiency

    Researchers have developed new algorithms for contextual combinatorial semi-bandit problems, which involve selecting subsets of arms to maximize cumulative rewards. One approach, proposed in a recent arXiv paper, offers…

  3. TOOL · CL_123263 ·

    New Convex Programming Method Finds Dense Submatrices in Complex Networks

    Researchers have developed a new method using convex programming to identify dense submatrices within larger matrices that contain multiple such dense regions. This approach extends previous work, which typically focuse…

  4. TOOL · CL_117139 ·

    New FALCON algorithm solves non-convex differential games for aerospace

    Researchers have developed FALCON, a novel algorithm designed to solve complex multi-agent optimal control problems, particularly those found in aerospace applications like pursuit-evasion and contested space operations…

  5. RESEARCH · CL_91216 ·

    New arXiv Papers Detail Advances in Convex Optimization Techniques

    Two new research papers on arXiv explore advancements in convex optimization. The first paper introduces a unified probing model for Online Convex Optimization (OCO) that can improve worst-case regret even with a sublin…

  6. RESEARCH · CL_20543 ·

    New methods enhance robust optimization with ensemble models and worst-case distribution analysis

    Researchers have developed new methods for distributionally robust optimization, a technique that accounts for uncertainty in data distributions. One approach, Ensemble Distributionally Robust Bayesian Optimization, use…