The paper proves that for resources with structural parallelizability (like divisibility and transferability), it is impossible to enforce a linear cost for concentrating influence, demonstrating that…

This paper introduces Neural Certificate Pricing (NCP), an unsupervised learning framework that exploits the asymmetry between certifiable discrete structures and structural feasibility in combinatori…

This paper introduces cost-aware Retrieval-Augmented Generation (RAG), demonstrating that fixed evidence selection is brittle and that adaptive, agentic controllers are necessary for effective knowled…

This paper introduces approximation-preserving coresets, which provide weaker guarantees than strong coresets but stronger guarantees than weak coresets for preserving the costs of good solutions in b…

This paper proposes an approximation algorithm for the submodular joint replenishment problem with decomposable submodular ordering cost functions, achieving an O(k)-approximation.

This paper studies the autarky problem of scheduling energy-consuming jobs with time windows using a battery and an energy forecast, and shows NP-hardness, polynomial-time solvability, and fixed-param…

This paper presents a compositional cost analysis for probabilistic programs with hierarchical cost structures, allowing computation of mean and higher moments of non-additive costs.

The paper presents an adaptive scaling algorithm with a competitive ratio of 1.373 for incremental submodular maximization under increasing cardinality constraint, improving upon the previous best res…

This study estimates the true social cost of corporate data breaches by quantifying the direct financial and opportunity costs to victims, finding that these costs can significantly exceed corporate s…

This paper presents a polynomial-time algorithm for recovering item values in the fractional knapsack problem using comparison queries, and provides a lower bound.

This paper introduces survey sampling techniques to estimate or minimize empirical pairwise loss functions, showing that targeting informative pairs significantly reduces computational cost while main…

This paper measures the integration friction in code repositories caused by autonomous coding agents and finds that about half of the variation in friction is repository-level, and agent-authored cont…

This paper introduces minimal additive codes over Fqh and establishes a one-to-one correspondence between minimal additive codes and additive strong blocking sets. It also compares this framework with…

This paper investigates the necessity of interaction for order-optimal 1-bit mean estimation in nonparametric finite-moment classes.

The paper establishes conditions for QUBO formulations of combinatorial optimization problems that guarantee valid binary and feasible local minimizers using gradient-based methods.

This paper develops statistical learning theory for gradient boosting in Peaks-over-Threshold modeling using Generalized Pareto distributions, deriving error bounds and reducing gradient correlation.

This paper improves the time complexity of exact algorithms for converting a connected graph into a cactus by reducing it from O*(3^n) to O*(2^n) for unweighted graphs, and provides faster algorithms…

The paper analyzes transaction fee mechanisms in modern blockchains that use parallel execution and contingency, proving an inherent trade-off between minimizing risks for users and maximizing revenue…