Near-tight (2/3-ε) approximation for identical-capacity bottleneck multiple knapsack and (1/2-ε) for arbitrary capacities, with matching inapproximability.
Mathematical Programming , volume =
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Establishes no-PTAS hardness for interval-restricted assignment and approximation thresholds of 48/47 and 1.5 for 2- and 4-resource restricted scheduling.
Global Bradley-Terry rankings of LLMs are misleading due to structured heterogeneity in user preferences, and small (λ, ν)-portfolios recover coherent subpopulations that cover over 96% of votes with just five rankings.
citing papers explorer
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Near-Tight Approximation Algorithms for Bottleneck Multiple Knapsack Problems
Near-tight (2/3-ε) approximation for identical-capacity bottleneck multiple knapsack and (1/2-ε) for arbitrary capacities, with matching inapproximability.
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Inapproximability Results for Scheduling with Interval and Resource Restrictions
Establishes no-PTAS hardness for interval-restricted assignment and approximation thresholds of 48/47 and 1.5 for 2- and 4-resource restricted scheduling.
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Why Global LLM Leaderboards Are Misleading: Small Portfolios for Heterogeneous Supervised ML
Global Bradley-Terry rankings of LLMs are misleading due to structured heterogeneity in user preferences, and small (λ, ν)-portfolios recover coherent subpopulations that cover over 96% of votes with just five rankings.