Optimization

Optimizing NOTEARS Objectives via Topological Swaps ICML 2023 Optimizing over trained GNNs via symmetry breaking NeurIPS 2023 Optimizing ROC Curves with a Sort-Based Surrogate Loss for Binary Classification and Changepoint Detection JMLR 2023 Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method NeurIPS 2023 Optimizing Test-Time Query Representations for Dense Retrieval ACL 2023 Optimizing the Computation of Overriding in DLN (Extended Abstract) IJCAI 2023 Optimizing the Placement of Roadside LiDARs for Autonomous Driving ICCV 2023 Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold COLT 2023 OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning IJCAI 2023 OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels CVPR 2023 OTF: Optimal Transport based Fusion of Supervised and Self-Supervised Learning Models for Automatic Speech Recognition Interspeech 2023 OTOv2: Automatic, Generic, User-Friendly ICLR 2023 Outlier Robust Adversarial Training ACML 2023 Outlier-Robust Gromov-Wasserstein for Graph Data NeurIPS 2023 Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling EMNLP 2023 Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron COLT 2023 Over-parameterized Model Optimization with Polyak-{\L}ojasiewicz Condition ICLR 2023 Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points ICML 2023 P1AC: Revisiting Absolute Pose From a Single Affine Correspondence ICCV 2023 PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023 PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile NeurIPS 2023 PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time AISTATS 2023 PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification ICLR 2023 PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023 Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation ICML 2023