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This work introduces cvxgenrust, an open-source tool for generating custom Rust code that solves families of parameterized convex optimization problems modeled in CVXPY, and generates a specialized Rust crate that updates parameters and calls Clarabel natively at runtime.
Data-driven driving simulators command accelerations and steering rates from a fixed grid without constraining the realized accelerations and jerks. As a result, reinforcement-learning policies inflate safety metrics through abrupt, last-second maneuvers that lie far outside the range of human driving and would be unac...
This work introduces a sampling-free, perturbation-based training framework based on continuous and differentiable masking that achieves competitive or superior attribution faithfulness compared to strong sampling-based baselines, while dramatically reducing computational cost and enabling substantially improved scalab...
DBLP is introduced, a symbolic framework that allows users to specify and solve optimistic bilevel problems in a high-level, human-readable way that is close to the mathematical formulation.
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