maximum cut
PulseAugur coverage of maximum cut — every cluster mentioning maximum cut across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New algorithms solve Max 2-SAT exactly in polynomial space
Researchers have developed new deterministic algorithms capable of solving Max 2-SAT instances exactly within polynomial space. These algorithms achieve an exponential time complexity of O*(2^((1-gamma)n)) for certain c…
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Learned optimizer schedules show distinct generalization patterns for MAX-CUT
Researchers have investigated the impact of state coupling in learned optimizer schedules for solving the MAX-CUT problem. Their study found that a state-blind schedule demonstrated strong generalization to larger insta…
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Graph Coarsening Method Enhances MAX-CUT Optimization
Researchers have developed a novel approach combining graph coarsening with Particle Polynomial Relaxation (PPR) to improve the optimization of nonconvex MAX-CUT problems. This method, utilizing Combinatorial Multigrid …
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New methods enable population-based architectures for neural combinatorial optimization
Researchers have developed new methods to integrate population-based strategies into neural combinatorial optimization. This approach aims to enhance the robustness and exploration capabilities of neural networks used f…
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New continuous relaxation method simplifies Ising problems for gradient-based optimization
Researchers have developed a novel continuous relaxation technique for Ising problems, which are foundational to many complex combinatorial challenges like MAX-CUT and Number Partitioning. This new method establishes a …
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Kernel PCA enhances QAOA parameter optimization for quantum computing
Researchers have explored Kernel Principal Component Analysis (KPCA) as a method to reduce the dimensionality of parameters for the Quantum Approximate Optimization Algorithm (QAOA). This technique aims to improve optim…
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New SDP solver SDPLR+ scales to million-variable problems
Researchers have developed a new semidefinite programming (SDP) solver called SDPLR+ that significantly improves scalability and speed for large-scale problems. This solver optimizes over low-rank factorizations, reduci…
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Adam optimization adapted for analog Ising machines
Researchers have developed continuous-time versions of the Adam optimization algorithm for use in analog Ising machines. These new dynamics aim to improve the speed and robustness of these machines, which are used for c…
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Research paper finds Baldwinian and Lamarckian evolution outperform Darwinian EAs
A new research paper revisits Lamarckian and Baldwinian evolution within evolutionary algorithms (EAs), comparing them against Darwinian evolution. Empirical results across six datasets for Maximum Independent Set and M…