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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)

LSDS++ : Dual Sampling for Accelerated k-means++ ICML 2023 LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs ICCV 2023 LVQAC: Lattice Vector Quantization Coupled With Spatially Adaptive Companding for Efficient Learned Image Compression CVPR 2023 M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery NeurIPS 2023 MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts AutoML 2023 Machine learning detects terminal singularities NeurIPS 2023 Machines of Finite Depth: Towards a Formalization of Neural Networks AAAI 2023 Macro Placement by Wire-Mask-Guided Black-Box Optimization NeurIPS 2023 MADG: Margin-based Adversarial Learning for Domain Generalization NeurIPS 2023 MADNet: Maximizing Addressee Deduction Expectation for Multi-Party Conversation Generation EMNLP 2023 MAG-GNN: Reinforcement Learning Boosted Graph Neural Network NeurIPS 2023 Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets EMNLP 2023 Make Landscape Flatter in Differentially Private Federated Learning CVPR 2023 Making Pre-trained Language Models both Task-solvers and Self-calibrators ACL 2023 Making Scalable Meta Learning Practical NeurIPS 2023 MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning JMLR 2023 Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds ICLR 2023 Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off NeurIPS 2023 MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization EMNLP 2023 MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters ICCV 2023 Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits NeurIPS 2023 Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations ICML 2023 Marginalized Importance Sampling for Off-Environment Policy Evaluation CoRL 2023 Markov Decision Processes with Time-Varying Geometric Discounting AAAI 2023 Markovian Gaussian Process Variational Autoencoders ICML 2023