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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)

Replicable Uniformity Testing NIPS 2024
Low Degree Hardness for Broadcasting on Trees NIPS 2024
Neural Network Reparametrization for Accelerated Optimization in Molecular Simulations NIPS 2024
Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling NIPS 2024
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics NIPS 2024
Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence NIPS 2024
Fast Best-of-N Decoding via Speculative Rejection NIPS 2024
PointMamba: A Simple State Space Model for Point Cloud Analysis NIPS 2024
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation NIPS 2024
Warm-starting Push-Relabel NIPS 2024
Latent Neural Operator for Solving Forward and Inverse PDE Problems NIPS 2024
Learning to compute Gröbner bases NIPS 2024
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation NIPS 2024
Neural Persistence Dynamics NIPS 2024
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs NIPS 2024
A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models NIPS 2024
Deep Equilibrium Algorithmic Reasoning NIPS 2024
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems NIPS 2024
Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks NIPS 2024
S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training NIPS 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NIPS 2024
Sparse maximal update parameterization: A holistic approach to sparse training dynamics NIPS 2024
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction NIPS 2024
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms NIPS 2024
Contextual Multinomial Logit Bandits with General Value Functions NIPS 2024