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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Adaptive Linear Estimating Equations NeurIPS 2023 Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction AAAI 2023 Adaptive Mixing of Auxiliary Losses in Supervised Learning AAAI 2023 Adaptive Optimization in the ∞-Width Limit ICLR 2023 Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo CVPR 2023 Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models AAAI 2023 Adaptive Plasticity Improvement for Continual Learning CVPR 2023 Adaptive Policy with Wait-k Model for Simultaneous Translation EMNLP 2023 Adaptive Positional Encoding for Bundle-Adjusting Neural Radiance Fields ICCV 2023 Adaptive Principal Component Regression with Applications to Panel Data NeurIPS 2023 Adaptive Regret for Control of Time-Varying Dynamics L4DC 2023 Adaptive Reordering Sampler with Neurally Guided MAGSAC ICCV 2023 Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting ACML 2023 Adaptive Rotated Convolution for Rotated Object Detection ICCV 2023 Adaptive Sample Selection for Robust Learning Under Label Noise WACV 2023 Adaptive Selective Sampling for Online Prediction with Experts NeurIPS 2023 Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction NeurIPS 2023 Adaptive Smoothing Gradient Learning for Spiking Neural Networks ICML 2023 Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds NeurIPS 2023 Adaptive Tuning for Metropolis Adjusted Langevin Trajectories AISTATS 2023 Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations NeurIPS 2023 Adaptive Zone-Aware Hierarchical Planner for Vision-Language Navigation CVPR 2023 A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models UAI 2023 AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning AAAI 2023 Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm ICML 2023