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Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Localized Zeroth-Order Prompt Optimization NIPS 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NIPS 2024
Neural Model Checking NIPS 2024
How many classifiers do we need? NIPS 2024
Discovering Preference Optimization Algorithms with and for Large Language Models NIPS 2024
Interventional Causal Discovery in a Mixture of DAGs NIPS 2024
Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NIPS 2024
Neur2BiLO: Neural Bilevel Optimization NIPS 2024
Analytically deriving Partial Information Decomposition for affine systems of stable and convolution-closed distributions NIPS 2024
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention NIPS 2024
Identifying Causal Effects Under Functional Dependencies NIPS 2024
Linear Regression using Heterogeneous Data Batches NIPS 2024
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NIPS 2024
Base of RoPE Bounds Context Length NIPS 2024
Learning Diffusion Priors from Observations by Expectation Maximization NIPS 2024
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models NIPS 2024
DAGER: Exact Gradient Inversion for Large Language Models NIPS 2024
Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting NIPS 2024
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NIPS 2024
Contextual Decision-Making with Knapsacks Beyond the Worst Case NIPS 2024
Transition Constrained Bayesian Optimization via Markov Decision Processes NIPS 2024
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games NIPS 2024
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise NIPS 2024
Speculative Monte-Carlo Tree Search NIPS 2024
Learning to Price Homogeneous Data NIPS 2024