Theory · optimization papers, 2023–2026

Key findings

• Theory · optimization went from 123 papers in 2023 to 584 in 2026, roughly 4.7x in three years.
• NeurIPS publishes the most Theory · optimization work: 778 papers from 2023 to 2026, 42% of the four-venue total.
• The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 0 in 2023 to 31 in 2026.
• Among the 5 topics under Theory and Statistics, it ranks #1 by 2026 paper count; the fastest grower in the group, Theory · learning theory, is up 5.6x versus 4.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
• ICML 2026A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
• ICLR 2026A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization
• CVPR 2026TriSim Tri-Dimensional Similarity Modeling with Extreme Value Theory for False-Negative
• NeurIPS 20253BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs
• ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
• ICLR 2025A Coefficient Makes SVRG Effective
• CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
• NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
• ICML 2024A Statistical Theory of Regularization-Based Continual Learning
• ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
• NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
• ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
• ICLR 2023Adaptive Optimization in the $\infty$-Width Limit
• CVPR 2023Deep Hashing With Minimal-Distance-Separated Hash Centers
• NeurIPS 2026Avoiding Obfuscation with Prover-Estimator Debate
• ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
• ICLR 2026A Memory-Efficient Hierarchical Algorithm for Large-scale Optimal Transport Problems
• CVPR 2026FedAdamom Adaptive Momentum for Improved Generalization in Federated Optimization
• NeurIPS 2025A Beyond-Worst-Case Analysis of Greedy k-means++

All Theory · optimization papers

1,871 papers, page 19 of 38

901. ICML 2025Radio: Rate–Distortion Optimization for Large Language Model Compression
902. ICML 2025Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
903. ICML 2025Reducing Variance of Stochastic Optimization for Approximating Nash Equilibria in Normal-Form Games
904. ICML 2025Retraining with Predicted Hard Labels Provably Increases Model Accuracy
905. ICML 2025Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness
906. ICML 2025Robust Sparsification via Sensitivity
907. ICML 2025ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
908. ICML 2025Safe-EF: Error Feedback for Non-smooth Constrained Optimization
909. ICML 2025Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
910. ICML 2025Scalable Meta-Learning via Mixed-Mode Differentiation
911. ICML 2025Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
912. ICML 2025Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers
913. ICML 2025SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
914. ICML 2025SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
915. ICML 2025SERENA: A Unified Stochastic Recursive Variance Reduced Gradient Framework for Riemannian Non-Convex Optimization
916. ICML 2025Sharp Optimality of Simple, Plug-in Estimation of the Fisher Information of a Smoothed Density
917. ICML 2025Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks
918. ICML 2025Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry
919. ICML 2025Sparse-pivot: Dynamic correlation clustering for node insertions
920. ICML 2025SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
921. ICML 2025Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization
922. ICML 2025Stochastic Deep Restoration Priors for Imaging Inverse Problems
923. ICML 2025Structured Preconditioners in Adaptive Optimization: A Unified Analysis
924. ICML 2025Subspace Optimization for Large Language Models with Convergence Guarantees
925. ICML 2025The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
926. ICML 2025The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
927. ICML 2025The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations
928. ICML 2025The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
929. ICML 2025Tilted Sharpness-Aware Minimization
930. ICML 2025Toward a Unified Theory of Gradient Descent under Generalized Smoothness
931. ICML 2025Towards a Formal Theory of Representational Compositionality
932. ICML 2025Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
933. ICML 2025Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
934. ICML 2025TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization
935. ICML 2025When to Forget? Complexity Trade-offs in Machine Unlearning
936. ICML 2025Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg
937. NeurIPS 20253BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs
938. NeurIPS 2025A Beyond-Worst-Case Analysis of Greedy k-means++
939. NeurIPS 2025A Computationally Viable Numerical Gradient-based Technique for Optimal Covering Problems
940. NeurIPS 2025A Difference-of-Convex Functions Approach to Energy-Based Iterative Reasoning
941. NeurIPS 2025A Geometric Analysis of PCA
942. NeurIPS 2025A Gradient Guided Diffusion Framework for Chance Constrained Programming
943. NeurIPS 2025A Learning-Augmented Dynamic Programming Approach for Orienteering Problem with Time Windows
944. NeurIPS 2025A Minimalist Example of Edge-of-Stability and Progressive Sharpening
945. NeurIPS 2025A Near-Optimal Algorithm for Decentralized Convex-Concave Finite-Sum Minimax Optimization
946. NeurIPS 2025A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
947. NeurIPS 2025A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization
948. NeurIPS 2025A Single-Loop Gradient Algorithm for Pessimistic Bilevel Optimization via Smooth Approximation
949. NeurIPS 2025A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
950. NeurIPS 2025A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models

FAQ

How many Theory · optimization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,871 in total: 123 in 2023, 494 in 2024, 670 in 2025, 584 in 2026.

How many Theory · optimization papers are at NeurIPS 2026?

NeurIPS 2026 has 119 Theory · optimization papers, versus 318 the year before.

How many Theory · optimization papers are at ICLR 2026?

ICLR 2026 has 244 Theory · optimization papers, versus 196 the year before.

How many Theory · optimization papers are at ICML 2026?

ICML 2026 has 214 Theory · optimization papers, versus 147 the year before.

How many Theory · optimization papers are at CVPR 2026?

CVPR 2026 has 7 Theory · optimization papers, versus 9 the year before.

Which conference publishes the most Theory · optimization papers?

NeurIPS, with 778 papers from 2023 to 2026.