Mathematics & Optimization

Concentration and Moment Inequalities for General Functions of Independent Random Variables with Heavy Tails JMLR 2024 Concentration Inequalities for General Functions of Heavy-Tailed Random Variables ICML 2024 Concentration of empirical barycenters in metric spaces ALT 2024 Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms IJCAI 2024 Conditional Adjustment in a Markov Equivalence Class AISTATS 2024 Conditional Bayesian Quadrature UAI 2024 Conditions for parameter unidentifiability of linear ARX systems for enhancing security L4DC 2024 Confidence Interval Estimation of Predictive Performance in the Context of AutoML AutoML 2024 Configurable Mirror Descent: Towards a Unification of Decision Making ICML 2024 Conformal Inverse Optimization NeurIPS 2024 Conformalized Multiple Testing after Data-dependent Selection NeurIPS 2024 Conformal Prediction Regions for Time Series Using Linear Complementarity Programming AAAI 2024 Conformal Predictions under Markovian Data ICML 2024 Confounded Budgeted Causal Bandits CLeaR 2024 Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion NeurIPS 2024 Consistency of Dictionary-Based Manifold Learning AISTATS 2024 Consistent Autoformalization for Constructing Mathematical Libraries EMNLP 2024 Consistent Multiclass Algorithms for Complex Metrics and Constraints JMLR 2024 Consistent Optimal Transport with Empirical Conditional Measures AISTATS 2024 Consistent Submodular Maximization ICML 2024 Constant Acceleration Flow NeurIPS 2024 Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication AISTATS 2024 Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence AAAI 2024 Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm ICLR 2024 Constrained Binary Decision Making NeurIPS 2024