Optimization

Physics-Driven ML-Based Modelling for Correcting Inverse Estimation NeurIPS 2023 PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NeurIPS 2023 PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching EMNLP 2023 Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion NeurIPS 2023 PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers AAAI 2023 Pixel-Wise Warping for Deep Image Stitching AAAI 2023 Plateau-Reduced Differentiable Path Tracing CVPR 2023 PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation CVPR 2023 PLOT: Prompt Learning with Optimal Transport for Vision-Language Models ICLR 2023 Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transport ICCV 2023 Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem AAAI 2023 Pointwise Mutual Information Based Metric and Decoding Strategy for Faithful Generation in Document Grounded Dialogs EMNLP 2023 Poisson Process for Bayesian Optimization AutoML 2023 Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes AAAI 2023 Policy Gradient for Rectangular Robust Markov Decision Processes NeurIPS 2023 Policy Gradient in Robust MDPs with Global Convergence Guarantee ICML 2023 Policy Optimization for Continuous Reinforcement Learning NeurIPS 2023 Polynomial Preconditioning for Gradient Methods ICML 2023 Pose-Free Neural Radiance Fields via Implicit Pose Regularization ICCV 2023 Posterior Tracking Algorithm for Classification Bandits AISTATS 2023 Post-Processing Temporal Action Detection CVPR 2023 PPR: Physically Plausible Reconstruction from Monocular Videos ICCV 2023 Practical Network Acceleration With Tiny Sets CVPR 2023 Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima NeurIPS 2023 Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows NeurIPS 2023