Optimization

Gradient descent in matrix factorization: Understanding large initialization UAI 2024 Gradient Guidance for Diffusion Models: An Optimization Perspective NeurIPS 2024 Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization NeurIPS 2024 High Probability and Risk-Averse Guarantees for a Stochastic Accelerated Primal-Dual Method JMLR 2024 How does PDE order affect the convergence of PINNs? NeurIPS 2024 How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization ICLR 2024 ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization CVPR 2024 Identification of Analytic Nonlinear Dynamical Systems with Non-asymptotic Guarantees NeurIPS 2024 Implications of Distance over Redistricting Maps: Central and Outlier Maps AAAI 2024 Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes NeurIPS 2024 Improving protein optimization with smoothed fitness landscapes ICLR 2024 Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates AAAI 2024 Inference in Probabilistic Answer Set Programs with Imprecise Probabilities via Optimization UAI 2024 INFORMEDQX: Informed Conflict Detection for Over-Constrained Problems AAAI 2024 InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimization CVPR 2024 Instance-Optimal Private Density Estimation in the Wasserstein Distance NeurIPS 2024 Interaction-Force Transport Gradient Flows NeurIPS 2024 Inversion-based Latent Bayesian Optimization NeurIPS 2024 Investigation into Training Dynamics of Learned Optimizers (Student Abstract) AAAI 2024 Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery AAAI 2024 Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NeurIPS 2024 Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization AAAI 2024 Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NeurIPS 2024 Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate AISTATS 2024 Large Language Models as Optimizers ICLR 2024