continuous optimization

A Scalable and Exact Relaxation for Densest k-Subgraph via Error Bounds AAAI 2026 Learning Stable Digraphs from Sparse-Input Linear Structural Causal Models UAI 2026 Scalable Air-Quality Sensor Placement via Gradient-Based Mutual Information Maximization AAAI 2026 Towards Fast and Scalable Normal Integration using Continuous Components WACV 2026 Augmented Mass-Spring Model for Real-Time Dense Hair Simulation ICCV 2025 Constrained Online Convex Optimization with Polyak Feasibility Steps ICML 2025 Continuous Structure Constraint Integration for Robust Causal Discovery AISTATS 2025 Data-Driven Performance Guarantees for Classical and Learned Optimizers JMLR 2025 DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces AAAI 2025 FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization ICCV 2025 MetricEmbedding: Accelerate Metric Nearness by Tropical Inner Product ICML 2025 MPO: Boosting LLM Agents with Meta Plan Optimization EMNLP 2025 ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization ICLR 2025 Utilitarian Algorithm Configuration for Infinite Parameter Spaces ICLR 2025 Adaptively Perturbed Mirror Descent for Learning in Games ICML 2024 Constraint-Free Structure Learning with Smooth Acyclic Orientations ICLR 2024 Differentiable Structure Learning with Partial Orders NeurIPS 2024 Dynamic Conditional Optimal Transport through Simulation-Free Flows NeurIPS 2024 Effective Causal Discovery under Identifiable Heteroscedastic Noise Model AAAI 2024 Implicit Bias of Mirror Flow on Separable Data NeurIPS 2024 Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models PGM 2024 Light Unbalanced Optimal Transport NeurIPS 2024 Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling NeurIPS 2024 Mirror and Preconditioned Gradient Descent in Wasserstein Space NeurIPS 2024 Online Markov Decision Processes Configuration with Continuous Decision Space AAAI 2024