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

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models NeurIPS 2024 Inherent limitations of dimensions for characterizing learnability of distribution classes COLT 2024 Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing NeurIPS 2024 Initialization Matters for Adversarial Transfer Learning CVPR 2024 Initialization of Large Language Models via Reparameterization to Mitigate Loss Spikes EMNLP 2024 Initializing Models with Larger Ones ICLR 2024 Initializing Services in Interactive ML Systems for Diverse Users NeurIPS 2024 Initializing Variable-sized Vision Transformers from Learngene with Learnable Transformation NeurIPS 2024 InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimization CVPR 2024 Ink Dot-Oriented Differentiable Optimization for Neural Image Halftoning CVPR 2024 Inlier Confidence Calibration for Point Cloud Registration CVPR 2024 Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models ICLR 2024 Input-gradient space particle inference for neural network ensembles ICLR 2024 Input Margins Can Predict Generalization Too AAAI 2024 In Search of a Data Transformation That Accelerates Neural Field Training CVPR 2024 In search of structure and correspondence in intra-speaker trial-to-trial variability Interspeech 2024 Insights from the Use of Previously Unseen Neural Architecture Search Datasets CVPR 2024 Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks AAAI 2024 Instance-Conditional Timescales of Decay for Non-Stationary Learning AAAI 2024 Instance-Optimal Private Density Estimation in the Wasserstein Distance NeurIPS 2024 Instances Need More Care: Rewriting Prompts for Instances with LLMs in the Loop Yields Better Zero-Shot Performance ACL 2024 Instance-Specific Asymmetric Sensitivity in Differential Privacy NeurIPS 2024 Instant Uncertainty Calibration of NeRFs Using a Meta-Calibrator ECCV 2024 InstructEval: Towards Holistic Evaluation of Instruction-Tuned Large Language Models EACL 2024 Instruction Fine-Tuning: Does Prompt Loss Matter? EMNLP 2024