NeurIPS 2025 Past Optimization
NeurIPS Workshop on GPU-Accelerated and Scalable Optimization
ScaleOPT
- Submission deadline
- Aug 23, 2025, 11:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (20)
Fetched from OpenReview (v2) on 2026-06-10.
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A Flow-Based Solver for Large-Scale Combinatorial Optimization
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AdamHD: Decoupled Huber Decay Regularization for Language Model Pre-Training
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AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library
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Alternative Learning Architecture for Solving AC-OPF via Supervised Relaxation and Cross Encoder
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Deterministic Continuous Replacement: Fast and Stable Module Replacement in Pretrained Transformers
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Entropy regularized subgame solving sequential Bayesian games with public actions
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Forking Sequences
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GPU Implementation of Second-Order Linear and Nonlinear Programming Solvers
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GPU-Accelerated Primal Heuristics for Mixed Integer Programming
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GPU-based Split algorithm for Large-Scale CVRPSD
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Learning to optimize over linearly convergent algorithms: gotta characterize 'em all
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MID-L: Matrix-Interpolated Dropout Layer with Layer-wise Neuron Selection
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MPAX: Mathematical Programming in JAX
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Nonlinear Optimization with GPU-Accelerated Neural Network Constraints
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On the Expressivity of GNN for Solving Second Order Cone Programming
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PEPFlow: A Python Library for the Workflow of Performance Estimation of Optimization Algorithms
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PRIME-RL: Async & Decentralized RL Training at Scale
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Quantum-Inspired Hamiltonian Descent for Mixed-Integer Quadratic Programming
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Quantum-Inspired Tensor Network Methods for Quadratic Unconstrained Binary Optimization
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ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization