A modular CPU-GPU batching framework for branch-and-bound delivers 10-100x speedups with zero optimality gap when certifying optimal cardinality-constrained GLMs.
Sparse regression at scale: Branch- and-bound rooted in first-order optimization.Mathematical Programming, 196(1):347–388
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From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs
A modular CPU-GPU batching framework for branch-and-bound delivers 10-100x speedups with zero optimality gap when certifying optimal cardinality-constrained GLMs.