Optimisation & control
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- Per-State Signatures and Mean Time-to-Failure: An Algorithm for Systems With Simultaneous Failures
- Event-Triggered Funnel Control for Output Reference Tracking of Unknown Nonlinear Systems
- Polarizable quasiconvex function generated metric projection
- Convergence Rates for Lasserre's Upper-Bound Hierarchy on ℝd with Gaussian Measure
- Defense Filters for Robust Learning of Partially Observed Dynamical Systems
- The Tilted Sampling Problem: Optimism, Posterior Sampling, and Logarithmic Regret
- GPU Parallel Pareto Local Search for Multi-objective QUBO
- Strong NP-Hardness of Rank-2 Nonnegative Matrix Factorization
- Provably Efficient Risk-Sensitive Offline Reinforcement Learning via Optimized Certainty Equivalents
- On the Complexity of Finding Stationary Points in Stochastic (L0, L1)-Smooth Nonconvex Optimization
- Data-driven Smooth-to-hard Spectral Regularization for General Linear Inverse Problems
- Optimal First-Order Methods for a Class of Structured Hölder-Smooth Problems
- Descending Everest with First-Order Oracles: Oracle Complexity of Convex Optimization under (L0,L1)-Smoothness
- An Alternating Minimization Algorithm for Federated Sparse Orthogonal Nonnegative Matrix Factorization
- Restarted Fixed-Point Acceleration of Proximal ADMM for Capped-ℓ1 Penalized Optimization
- Kernel-Based Heterogeneous Mean Field Games on a Continuum Type Space
- Optimization of a Perturbed Implicit Sweeping Process by Constrained Discontinuous Controls
- Observability as a constraint qualification for a nonsmooth bilevel PDE-constrained problem
- Dual Representations and Proxy Characterization of H2 Norm for Partial Integral Equations
- Honesty is the Best Policy ... or is it? Demand Management for Probabilistic Service Options
- Matrix Completion Discriminants
- When is a better LLM worth paying for? Stochastic Optimization with Switching Mixed-Fidelity Oracles
- Identifiability of a dissipative knowledge-dynamics model: exact recovery under designed excitation, degeneration on observational data
- CNet: A Complex-Valued Deep Learning Framework with Wirtinger Autodifferentiation and FFT--Hadamard Convolution
- Unique Minimizers for Permanents, Mixed Discriminants, and Log-concave Polynomials