mlsanityData to 7 Oct 2026

CVXPY: A Python-Embedded Modeling Language for Convex Optimization

arXiv 1603.00943 ↗First posted 3 Mar 2016math.OCcited by 633

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Abstract (arXiv)

CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples.

Key facts. Cited by 633 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Mar 2016.

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Citing papers per year: 2019: 1; 2020: 1; 2021: 91; 2022: 104; 2023: 119; 2024: 128; 2025: 115; 2026: 74.

633 papers.

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  2. 2021Efficient and Modular Implicit Differentiationcited by 199
  3. 2021On Calibration and Out-of-domain Generalizationcited by 134
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  6. 2022Robust Training under Label Noise by Over-parameterizationcited by 93
  7. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunitiescited by 83
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  9. 2019Policy Poisoning in Batch Reinforcement Learning and Controlcited by 70
  10. 2021Post-processing for Individual Fairnesscited by 61
  11. 2022Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Modelscited by 56
  12. 2022Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experimentscited by 50
38 more
  1. 2022Fair and Optimal Classification via Post-Processingcited by 50
  2. 2023How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Controlcited by 50
  3. 2021CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraintscited by 49
  4. 2024Autoformulation of Mathematical Optimization Models Using LLMscited by 48
  5. 2021Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Trackingcited by 47
  6. 2021Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspectivecited by 47
  7. 2022Predictive Multiplicity in Probabilistic Classificationcited by 44
  8. 2021Reachability Analysis of Neural Feedback Loopscited by 41
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  10. 2021Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementationcited by 40
  11. 2022SAM as an Optimal Relaxation of Bayescited by 40
  12. 2021Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivitycited by 39
  13. 2023OptiMUS: Optimization Modeling Using MIP Solvers and large language modelscited by 39
  14. 2024OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scalecited by 37
  15. 2023Policy Optimization in RLHF: The Impact of Out-of-preference Datacited by 35
  16. 2025Implicit Bias of Spectral Descent and Muon on Multiclass Separable Datacited by 33
  17. 2021ViTAS: Vision Transformer Architecture Searchcited by 31
  18. 2022Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositionscited by 31
  19. 2022A General Framework for Sample-Efficient Function Approximation in Reinforcement Learningcited by 31
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  24. 2022Gaussian Universality of Perceptrons with Random Labelscited by 26
  25. 2021Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programscited by 25
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  30. 2021BCNet: Searching for Network Width with Bilaterally Coupled Networkcited by 23
  31. 2021Implicit differentiation for fast hyperparameter selection in non-smooth convex learningcited by 22
  32. 2021Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPscited by 22
  33. 2022Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfecited by 22
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  36. 2022Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfercited by 22
  37. 2021Discovering a set of policies for the worst case rewardcited by 21
  38. 2021Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularizationcited by 21

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