SeqRejectron constructs a stopping rule with a small set of validator policies to achieve horizon-free sample complexity for selective imitation learning under arbitrary dynamics shifts.
2019 18th European control conference (ECC) , pages=
6 Pith papers cite this work. Polarity classification is still indexing.
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2026 6representative citing papers
HyperCertificates combine closure certificates for lookahead with barrier and ranking functions to verify discrete-time systems against HyperLTL specifications.
Gives necessary and sufficient exactness certificates based on primal and dual feasibility for when a violated-set closed-form correction equals the exact Euclidean projection in CBF safety filters.
Geometric Pareto Control embeds Pareto solutions in a Lie group submanifold and navigates via Riemannian gradient flow to achieve 100% feasibility and low suboptimality in control tasks without retraining.
LightCROWN computes tighter Jacobian bounds for neural networks with smooth nonlinear activations by exploiting their analytical properties, raising verification success rates for neural control barrier functions up to 100% on benchmark control systems.
A single boundary controller for the LWR traffic model is not certified by the main theorems, because the proof omits endpoint optima and mishandles infeasibility of the stability constraint.
citing papers explorer
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Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
SeqRejectron constructs a stopping rule with a small set of validator policies to achieve horizon-free sample complexity for selective imitation learning under arbitrary dynamics shifts.
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HyperCertificates: Verification of Discrete-time Dynamical Systems against HyperLTL Specifications
HyperCertificates combine closure certificates for lookahead with barrier and ranking functions to verify discrete-time systems against HyperLTL specifications.
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Exactness Certificates for Closed-Form CBF Safety-Filter Projections
Gives necessary and sufficient exactness certificates based on primal and dual feasibility for when a violated-set closed-form correction equals the exact Euclidean projection in CBF safety filters.
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Geometric Pareto Control: Riemannian Gradient Flow of Energy Function via Lie Group Homotopy
Geometric Pareto Control embeds Pareto solutions in a Lie group submanifold and navigates via Riemannian gradient flow to achieve 100% feasibility and low suboptimality in control tasks without retraining.
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Efficient Verification of Neural Control Barrier Functions with Smooth Nonlinear Activations
LightCROWN computes tighter Jacobian bounds for neural networks with smooth nonlinear activations by exploiting their analytical properties, raising verification success rates for neural control barrier functions up to 100% on benchmark control systems.
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Optimization-based One-side Boundary Control of LWR Traffic Models
A single boundary controller for the LWR traffic model is not certified by the main theorems, because the proof omits endpoint optima and mishandles infeasibility of the stability constraint.