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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)

A Kernel Stein Test of Goodness of Fit for Sequential Models ICML 2023 A Large-Scale Homography Benchmark CVPR 2023 A Large-Scale Study of Probabilistic Calibration in Neural Network Regression ICML 2023 A Latent-Variable Model for Intrinsic Probing AAAI 2023 A law of adversarial risk, interpolation, and label noise ICLR 2023 A Law of Robustness beyond Isoperimetry ICML 2023 A Learnable Radial Basis Positional Embedding for Coordinate-MLPs AAAI 2023 A Learning and Control Perspective for Microfinance L4DC 2023 Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions NeurIPS 2023 ALERT: Adapt Language Models to Reasoning Tasks ACL 2023 Algebraically Rigorous Quaternion Framework for the Neural Network Pose Estimation Problem ICCV 2023 Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation AISTATS 2023 Algorithm for Constrained Markov Decision Process with Linear Convergence AISTATS 2023 Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge (Extended Abstract) IJCAI 2023 Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler COLT 2023 Algorithmic Collective Action in Machine Learning ICML 2023 Algorithmic Gaussianization through Sketching: Converting Data into Sub-gaussian Random Designs COLT 2023 Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing NeurIPS 2023 Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions ICML 2023 Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares ALT 2023 Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations CVPR 2023 AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation Interspeech 2023 Aligning Language Models with Preferences through f-divergence Minimization ICML 2023 Aligning Large Language Models through Synthetic Feedback EMNLP 2023 Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation NeurIPS 2023