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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

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

Random Fully Connected Neural Networks as Perturbatively Solvable Hierarchies JMLR 2024 Random Function Descent NeurIPS 2024 Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces NeurIPS 2024 Randomized Confidence Bounds for Stochastic Partial Monitoring ICML 2024 Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NeurIPS 2024 Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy NeurIPS 2024 Randomized Strategic Facility Location with Predictions NeurIPS 2024 Randomized Truthful Auctions with Learning Agents NeurIPS 2024 Random matrix theory improved Fréchet mean of symmetric positive definite matrices ICML 2024 Random Oscillators Network for Time Series Processing AISTATS 2024 Random Scaling and Momentum for Non-smooth Non-convex Optimization ICML 2024 Random Smoothing Regularization in Kernel Gradient Descent Learning JMLR 2024 Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks ICLR 2024 RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Losses CVPR 2024 Rapid Learning without Catastrophic Forgetting in the Morris Water Maze ICML 2024 RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting NeurIPS 2024 Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling CoRL 2024 Rates of convergence for density estimation with generative adversarial networks JMLR 2024 RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models EMNLP 2024 READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling AAAI 2024 Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization ICML 2024 Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer NeurIPS 2024 realSEUDO for real-time calcium imaging analysis NeurIPS 2024 Real-Time Recurrent Learning using Trace Units in Reinforcement Learning NeurIPS 2024 Real-time safe control of neural network dynamic models with sound approximation L4DC 2024