The paper proposes a novel Bayesian framework to learn the optimal decision strategy for the stochastic shortest path problem by directly constructing the posterior beliefs for the action-value functi…

The paper introduces a diffusion-based uncertainty model for robust optimization on graphs, showing that the resulting computational complexity depends critically on the interaction between the uncert…

The paper proposes a fuzzy modeling framework using subnormal Gaussian fuzzy numbers to prioritize IDS alerts by explicitly incorporating threat severity, detection confidence, and organizational risk…

The paper introduces R$^2$A, an adversarial attack that uses suffix optimization to mislead black-box LLM routers into consistently selecting expensive, high-capability models.

This paper introduces a new variant of the Traveling Salesman Problem where the goal is to find two paths connecting a set of sites while minimizing the Fréchet distance between the two paths.

The paper introduces PRAXIS, a novel algorithm that efficiently approximates the computation of 'Rashomon sets' for decision trees, significantly reducing memory and runtime complexity.

The paper presents an end-to-end system that translates high-level operator intents into low-level, safe routing constraints for LEO mega-constellations, achieving high accuracy and safety guarantees.

The paper proposes an uncertainty-aware, decentralized fusion layer for multi-UAV systems that significantly improves 3D localization robustness by incorporating neighbor constraints and handling faul…

The paper proposes GC-MoE, a graph-conditioned Mixture of Experts framework, to improve traffic forecasting by assigning personalized, specialized forecasting experts to individual road segments.

The paper analyzes the structured CVP distance on the log-unit lattice of cyclotomic fields, significantly reducing the conjectured CDPR factor for the ML-KEM cryptosystem from exponential to sub-poly…

PSG-Nav addresses open-vocabulary navigation uncertainty by constructing a 3D Probabilistic Scene Graph and using Multiverse Decision Making to sample multiple possible world settings for robust, glob…

This paper settles the complexity of three sketching problems in graphs and distributions.

The paper analyzes preference-shaped expected improvement criteria for Bayesian multiobjective optimization, precisely characterizing when transformations preserve key properties like exact computatio…

The paper proposes S3TS, a novel tree search algorithm that simultaneously handles both non-linear system models and explicit uncertainties (scenarios) for advanced energy planning, achieving near-opt…

The paper proposes a novel Large Neighborhood Search (LNS) method, incorporating hybrid destroy operators and an exact repair solver, to effectively solve the Capacitated Facility Location Problem wit…

This paper addresses the security vulnerabilities in drone swarm control algorithms by proposing two fuzzing tools, SwarmFuzzGraph and SwarmFuzzBinary, to discover Swarm Propagation Vulnerabilities (S…

AlphaTransit introduces a novel search-based planning framework that combines Monte Carlo Tree Search (MCTS) with a neural policy-value network to efficiently design high-quality, city-scale bus trans…

The paper evaluates dynamic coordination strategy selection for enterprise multi-agent systems, finding that a calibrated default routing approach is effective, even if a deterministic winner-selectio…

The paper proposes a semi-relaxed Gromov-Wasserstein objective to estimate the latent connectivity structure of large-scale networks, achieving statistically consistent and efficient recovery of the u…