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