Deep learning · optimization papers, 2023–2026
Deep learning area: optimization
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 953 papers are tagged with this topic.
Key findings
- Deep learning · optimization fell from 256 papers in 2023 to 240 in 2026, so interest is cooling.
- NeurIPS publishes the most Deep learning · optimization work: 500 papers from 2023 to 2026, 52% of the four-venue total.
- The fastest-growing overlap is with Alignment and Safety: papers tagged with both rose from 5 in 2023 to 23 in 2026.
- Among the 11 topics under Deep Learning, it ranks #6 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.9x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 144 | 34 | 70 | 8 | 256 |
| 2024 | 191 | 30 | 72 | 1 | 294 |
| 2025 | 62 | 51 | 44 | 6 | 163 |
| 2026 | 103 | 44 | 86 | 7 | 240 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026Achieving Directional-Stationarity from a Single Random Direction Step
- ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
- ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
- CVPR 2026Coverage Optimization for Camera View Selection
- NeurIPS 2025High-Performance Arithmetic Circuit Optimization via Differentiable Architecture Search
- ICML 2025Feature-Mapping Topology Optimization with Neural Heaviside Signed Distance Functions
- ICLR 2025Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
- CVPR 2025HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition
- NeurIPS 2024$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
- ICML 2024Barrier Algorithms for Constrained Non-Convex Optimization
- ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
- CVPR 2024Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
- NeurIPS 2023$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning
- ICML 2023Buying Information for Stochastic Optimization
- ICLR 2023Alternating Differentiation for Optimization Layers
- CVPR 2023Visual-Language Prompt Tuning With Knowledge-Guided Context Optimization
- NeurIPS 2026Adaptive Conditional Gradient Sliding: Projection-Free and Line-Search-Free Acceleration
- ICML 2026Riemannian Optimization for Fair Spectral Clustering
- ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
- CVPR 2026Its Never Too Late Noise Optimization for Collapse Recovery in
All Deep learning · optimization papers
272 papers, page 5 of 6
- ICML 2024Vanilla Bayesian Optimization Performs Great in High Dimensions
- ICML 2024Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
- ICML 2023A Distribution Optimization Framework for Confidence Bounds of Risk Measures
- ICML 2023A Fully First-Order Method for Stochastic Bilevel Optimization
- ICML 2023Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
- ICML 2023Accelerated Stochastic Optimization Methods under Quasar-convexity
- ICML 2023Automatically Auditing Large Language Models via Discrete Optimization
- ICML 2023Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization
- ICML 2023Beyond Reward: Offline Preference-guided Policy Optimization
- ICML 2023Beyond Uniform Lipschitz Condition in Differentially Private Optimization
- ICML 2023Bilevel Optimization with Coupled Decision-Dependent Distributions
- ICML 2023Bit Allocation using Optimization
- ICML 2023Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization
- ICML 2023Buying Information for Stochastic Optimization
- ICML 2023Competitive Gradient Optimization
- ICML 2023Constrained Efficient Global Optimization of Expensive Black-box Functions
- ICML 2023Continuation Path Learning for Homotopy Optimization
- ICML 2023Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data
- ICML 2023Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
- ICML 2023DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization
- ICML 2023Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity
- ICML 2023Differentially Private Optimization on Large Model at Small Cost
- ICML 2023Differentially Private Stochastic Convex Optimization under a Quantile Loss Function
- ICML 2023Diffusion Models for Black-Box Optimization
- ICML 2023Dynamic Constrained Submodular Optimization with Polylogarithmic Update Time
- ICML 2023Efficient displacement convex optimization with particle gradient descent
- ICML 2023Escaping saddle points in zeroth-order optimization: the power of two-point estimators
- ICML 2023Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
- ICML 2023Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
- ICML 2023Faster Rates of Convergence to Stationary Points in Differentially Private Optimization
- ICML 2023FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization
- ICML 2023FeDXL: Provable Federated Learning for Deep X-Risk Optimization
- ICML 2023Generalized Polyak Step Size for First Order Optimization with Momentum
- ICML 2023Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization
- ICML 2023Generative Pretraining for Black-Box Optimization
- ICML 2023Global Optimization with Parametric Function Approximation
- ICML 2023Global Selection of Contrastive Batches via Optimization on Sample Permutations
- ICML 2023Improving Bi-level Optimization Based Methods with Inspiration from Humans' Classroom Study Techniques
- ICML 2023Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
- ICML 2023Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement
- ICML 2023Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach
- ICML 2023Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability
- ICML 2023Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization
- ICML 2023Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes
- ICML 2023Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
- ICML 2023Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization
- ICML 2023Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods
- ICML 2023Omnipredictors for Constrained Optimization
- ICML 2023On User-Level Private Convex Optimization
- ICML 2023Optimal Shrinkage for Distributed Second-Order Optimization
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FAQ
- How many Deep learning · optimization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 953 in total: 256 in 2023, 294 in 2024, 163 in 2025, 240 in 2026.
- How many Deep learning · optimization papers are at NeurIPS 2026?
- NeurIPS 2026 has 103 Deep learning · optimization papers, versus 62 the year before.
- How many Deep learning · optimization papers are at ICLR 2026?
- ICLR 2026 has 44 Deep learning · optimization papers, versus 51 the year before.
- How many Deep learning · optimization papers are at ICML 2026?
- ICML 2026 has 86 Deep learning · optimization papers, versus 44 the year before.
- How many Deep learning · optimization papers are at CVPR 2026?
- CVPR 2026 has 7 Deep learning · optimization papers, versus 6 the year before.
- Which conference publishes the most Deep learning · optimization papers?
- NeurIPS, with 500 papers from 2023 to 2026.
More in Deep Learning
- Diffusion Models 6,900
- Deep learning · generative models and autoencoders 4,314
- Deep learning · large language models 2,334
- Deep learning · self supervised learning 1,958
- Deep learning · graph neural networks 1,648
- Deep learning · representation learning 802
- Deep learning · probabilistic methods 637
- Deep learning · foundation models 536
- Deep learning · causal inference 316
- Deep learning · transfer learning 197