Awesome Optimization & Control

The Spectral Dynamics and Noise Geometry of Muon (2026)

Pierfrancesco Beneventano et al.

9.07

p-PSO: A Penalized Particle Swarm Optimization Technique for Finding D-Optimal Designs with Mixed Factors in Generalized Linear Models (2026)

Shrabanti Chowdhury et al.

4.39

Machine learning enables roughness-driven inverse design of milling processes (2026)

Hadi Bakhshan et al.

4.39

LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization (2026)

Mingen Kuang et al.

3.51

Residual-Controlled Multiplier Learning for Stochastic Constrained Decision-Making (2026)

Kang Liu et al.

3.51

Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs (2026)

Tianhao Wu et al.

3.51

Schattor: Schatten-family methods for deep learning optimization (2026)

Bohao Ma et al.

3.51

Functional Gradient Descent with Adaptive Representations (2026)

Daniel Csillag et al.

3.51

PER-DPP Sampling Framework and Its Application in Path Planning (2025)

Junzhe Wang

2.76

Improving Feasibility via Fast Autoencoder-Based Projections (2026)

Maria Chzhen et al.

1.89

NS-RGS: Newton-Schulz based Riemannian gradient method for orthogonal group synchronization (2026)

Haiyang Peng et al.

1.89

New Hybrid Fine-Tuning Paradigm for LLMs: Algorithm Design and Convergence Analysis Framework (2026)

Shaocong Ma et al.

1.89

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control (2026)

Julian Skifstad et al.

1.89

Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning (2026)

Yicheng Pan et al.

1.89

Feed m Birds with One Scone: Accelerating Multi-task Gradient Balancing via Bi-level Optimization (2026)

Xuxing Chen et al.

1.83

A Learning Method with Gap-Aware Generation for Heterogeneous DAG Scheduling (2026)

Ruisong Zhou et al.

1.83

Mitigating Forgetting in Continual Learning with Selective Gradient Projection (2026)

Anika Singh et al.

1.83

Quality-Diversity Optimization as Multi-Objective Optimization (2026)

Xi Lin et al.

1.78

Soft-Radial Projection for Constrained End-to-End Learning (2026)

Philipp J. Schneider et al.

1.78

Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods (2026)

Grigory Begunov et al.

1.78

Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning (2026)

Oswin So et al.

1.78

Learning to accelerate Krasnosel'skii-Mann fixed-point iterations with guarantees (2026)

Andrea Martin et al.

1.72

Accelerated Methods with Complexity Separation Under Data Similarity for Federated Learning Problems (2026)

Dmitry Bylinkin et al.

1.72

Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming (2025)

Ningwei Bai et al.

1.67

Scaling up Stability: Reinforcement Learning for Distributed Control of Networked Systems in the Space of Stabilizing Policies (2025)

John Cao et al.

1.67

Active Constraint Learning in High Dimensions from Demonstrations (2025)

Zheng Qiu et al.

1.67

A Modular Algorithm for Non-Stationary Online Convex-Concave Optimization (2025)

Qing-xin Meng et al.

1.50

Joint Cooperative and Non-Cooperative Localization in WSNs with Distributed Scaled Proximal ADMM Algorithms (2025)

Qiaojia Zhu et al.

1.50

Zero-Shot Transferable Solution Method for Parametric Optimal Control Problems (2025)

Xingjian Li et al.

1.50

Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent (2025)

Tong Yang et al.

1.44

HiFo-Prompt: Prompting with Hindsight and Foresight for LLM-based Automatic Heuristic Design (2025)

Chentong Chen et al.

1.44

Jointly Computation- and Communication-Efficient Distributed Learning (2025)

Xiaoxing Ren et al.

1.44

AdLoCo: adaptive batching significantly improves communications efficiency and convergence for Large Language Models (2025)

Nikolay Kutuzov et al.

1.44

Information Preserving Line Search via Bayesian Optimization (2025)

Robin Labryga and Tomislav Prusina and S\"oren Laue

1.39

ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search (2025)

Olivia Dry et al.

1.39

A Generic Branch-and-Bound Algorithm for $\ell_0$-Penalized Problems with Supplementary Material (2025)

Cl\'ement Elvira et al.

1.33

Yuki Takezawa et al.

1.33

Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL) (2025)

Nihal Acharya Adde et al.

1.33

DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty (2025)

Mingxuan Cui et al.

1.33

Latency-aware 2-opt Monotonic Local Search For Distributed Constraint Optimization (2025)

Ben Rachmut, Roie Zivan, William Yeoh

1.33

Rank-One Modified Value Iteration (2025)

Arman Sharifi Kolarijani et al.

1.28

SEvoBench : A C++ Framework For Evolutionary Single-Objective Optimization Benchmarking (2025)

Yongkang Yang et al.

1.28

Fast MLE and MAPE-Based Device Activity Detection for Grant-Free Access via PSCA and PSCA-Net (2025)

Bowen Tan and Ying Cui

1.17

ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning (2025)

Artavazd Maranjyan et al.

1.11

LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM (2025)

Yehonathan Refael et al.

1.11

When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach (2025)

Qian Chen et al.

1.06

PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization (2018)

Balaji Sesha Sarath Pokuri et al.

—

From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization (2019)

Krzysztof Choromanski et al.

—

Uncertainty-aware Model-based Policy Optimization (2019)

Tung-Long Vuong and Kenneth Tran

—

Efficient Learning of Distributed Linear-Quadratic Controllers (2019)

Salar Fattahi and Nikolai Matni and Somayeh Sojoudi

—

Global-Local Metamodel Assisted Two-Stage Optimization via Simulation (2019)

Wei Xie et al.

—

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization (2019)

Ali Kavis et al.

—

Asynchronous and Parallel Distributed Pose Graph Optimization (2020)

Yulun Tian et al.

—

A General Large Neighborhood Search Framework for Solving Integer Linear Programs (2020)

Jialin Song et al.

—

Multilevel Minimization for Deep Residual Networks (2020)

Lisa Gaedke-Merzh\"auser and Alena Kopani\v{c}\'akov\'a and Rolf Krause

—

Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control (2020)

Giorgos Mamakoukas et al.

—

Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization (2020)

Samuel Daulton et al.

—

Partial Policy Iteration for L1-Robust Markov Decision Processes (2020)

Chin Pang Ho and Marek Petrik and Wolfram Wiesemann

—

Hyperparameter Optimization via Sequential Uniform Designs (2020)

Zebin Yang and Aijun Zhang

—

Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems (2021)

Siavash Alemzadeh et al.

—

Key papers