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

Continual learning with the neural tangent ensemble NeurIPS 2024 Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation ICLR 2024 Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks ICLR 2024 Continuous Prediction with Experts' Advice JMLR 2024 Continuous Product Graph Neural Networks NeurIPS 2024 Continuous Relational Diffusion Driven Topic Model with Multi-grained Text for Microblog COLING 2024 Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation NeurIPS 2024 Contracting with a Learning Agent NeurIPS 2024 Contrastive Learning is Spectral Clustering on Similarity Graph ICLR 2024 Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion EMNLP 2024 Contrastive Predict-and-Search for Mixed Integer Linear Programs ICML 2024 Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation ICML 2024 Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms L4DC 2024 Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment EMNLP 2024 Controllable Prompt Tuning For Balancing Group Distributional Robustness ICML 2024 Controllable Text Generation with Residual Memory Transformer ACL 2024 Controlled maximal variability along with reliable performance in recurrent neural networks NeurIPS 2024 Controlling Continuous Relaxation for Combinatorial Optimization NeurIPS 2024 Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NeurIPS 2024 Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model WACV 2024 ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence NeurIPS 2024 Convergence Analysis of Split Federated Learning on Heterogeneous Data NeurIPS 2024 Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms ICML 2024 Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point ICML 2024 Convergence Behavior of an Adversarial Weak Supervision Method UAI 2024