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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)

UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection ACL 2024 Validating Climate Models with Spherical Convolutional Wasserstein Distance NeurIPS 2024 Value at Adversarial Risk: A Graph Defense Strategy against Cost-Aware Attacks AAAI 2024 Value-Distributional Model-Based Reinforcement Learning JMLR 2024 ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation ICLR 2024 Vanilla Bayesian Optimization Performs Great in High Dimensions ICML 2024 Vanishing Gradients in Reinforcement Finetuning of Language Models ICLR 2024 Variance estimation in compound decision theory under boundedness NeurIPS 2024 Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions ICLR 2024 Variational Bayesian Last Layers ICLR 2024 Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024 Variational Gaussian Process Diffusion Processes AISTATS 2024 Variational Inference for SDEs Driven by Fractional Noise ICLR 2024 Variational Inference with Coverage Guarantees in Simulation-Based Inference ICML 2024 Variational Learning is Effective for Large Deep Networks ICML 2024 Variational Linearized Laplace Approximation for Bayesian Deep Learning ICML 2024 Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NeurIPS 2024 Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts ICML 2024 Variational Resampling AISTATS 2024 Variational Schrödinger Diffusion Models ICML 2024 VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition ICLR 2024 VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates AISTATS 2024 VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections NeurIPS 2024 VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch AAAI 2024 Verifiable, Debuggable, and Repairable Commonsense Logical Reasoning via LLM-based Theory Resolution EMNLP 2024