#Optimization
Latest news articles tagged with "Optimization". Follow the timeline of events, related topics, and entities.
Articles (17)
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🇺🇸 Survey on Neural Routing Solvers
[USA]
arXiv:2602.21761v1 Announce Type: cross Abstract: Neural routing solvers (NRSs) that leverage deep learning to tackle vehicle routing problems have demonstrated notable potential for practical applic...
Related: #Artificial Intelligence, #Machine Learning -
🇺🇸 Enhancing CVRP Solver through LLM-driven Automatic Heuristic Design
[USA]
arXiv:2602.23092v1 Announce Type: new Abstract: The Capacitated Vehicle Routing Problem (CVRP), a fundamental combinatorial optimization challenge, focuses on optimizing fleet operations under vehicl...
Related: #Artificial Intelligence, #Vehicle Routing -
🇺🇸 ConstraintBench: Benchmarking LLM Constraint Reasoning on Direct Optimization
[USA]
arXiv:2602.22465v1 Announce Type: new Abstract: Large language models are increasingly applied to operational decision-making where the underlying structure is constrained optimization. Existing benc...
Related: #AI Benchmarking, #Constraint Reasoning -
🇺🇸 Understanding Transformer Optimization via Gradient Heterogeneity
[USA]
arXiv:2502.00213v4 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite t...
Related: #Transformers, #Gradient heterogeneity, #Adaptive optimizers, #Stochastic gradient descent -
🇺🇸 Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer
[USA]
arXiv:2602.15451v1 Announce Type: cross Abstract: Deep generative modeling to stochastically design small molecules is an emerging technology for accelerating drug discovery and development. However,...
Related: #Generative AI, #Quantum Annealing, #Molecular Design, #Drug Discovery -
🇺🇸 Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
[USA]
arXiv:2602.12586v1 Announce Type: new Abstract: While plan-and-infill decoding in Masked Diffusion Models (MDMs) shows promise for mathematical and code reasoning, performance remains highly sensitiv...
Related: #Artificial Intelligence, #Natural Language Processing -
🇺🇸 EvoCut: Strengthening Integer Programs via Evolution-Guided Language Models
[USA]
arXiv:2508.11850v2 Announce Type: replace Abstract: Integer programming (IP) is central to many combinatorial optimization tasks but remains challenging due to its NP-hard nature. A practical way to ...
Related: #Artificial Intelligence, #Automation -
🇺🇸 Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
[USA]
arXiv:2602.00737v2 Announce Type: replace-cross Abstract: Multi-objective optimization (MOO) arises in many real-world applications where trade-offs between competing objectives must be carefully bal...
Related: #Machine Learning, #Artificial Intelligence -
🇺🇸 BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability
[USA]
arXiv:2602.07144v1 Announce Type: cross Abstract: Bayesian optimization (BO) is a popular technique for sample-efficient optimization of black-box functions. In many applications, the parameters bein...
Related: #Machine Learning, #Artificial Intelligence -
🇺🇸 G-LNS: Generative Large Neighborhood Search for LLM-Based Automatic Heuristic Design
[USA]
arXiv:2602.08253v1 Announce Type: new Abstract: While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing approaches typically formulate AHD around ...
Related: #Artificial Intelligence, #Computer Science -
🇺🇸 The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
[USA]
arXiv:2602.07078v1 Announce Type: cross Abstract: Reinforcement Learning (RL) for Large Language Models (LLMs) often suffers from training collapse in long-horizon tasks due to exploding gradient var...
Related: #Artificial Intelligence, #Machine Learning -
🇺🇸 Mimetic Initialization of MLPs
[USA]
arXiv:2602.07156v1 Announce Type: cross Abstract: Mimetic initialization uses pretrained models as case studies of good initialization, using observations of structures in trained weights to inspire ...
Related: #Machine Learning, #Artificial Intelligence -
🇺🇸 iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems
[USA]
arXiv:2602.06064v1 Announce Type: cross Abstract: Scheduling precedence-constrained tasks under shared renewable resources is central to modern computing platforms. The Resource Investment Problem (R...
Related: #Artificial Intelligence, #Cloud Computing -
🇺🇸 Target noise: A pre-training based neural network initialization for efficient high resolution learning
[USA]
arXiv:2602.06585v1 Announce Type: cross Abstract: Weight initialization plays a crucial role in the optimization behavior and convergence efficiency of neural networks. Most existing initialization m...
Related: #Machine Learning, #Artificial Intelligence -
🇺🇸 Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance
[USA]
arXiv:2602.05774v1 Announce Type: cross Abstract: Speculative decoding accelerates inference for (M)LLMs, yet a training-decoding discrepancy persists: while existing methods optimize single greedy t...
Related: #Artificial Intelligence, #Machine Learning -
🇺🇸 Enterprise Resource Planning Using Multi-type Transformers in Ferro-Titanium Industry
[USA]
arXiv:2601.20696v1 Announce Type: new Abstract: Combinatorial optimization problems such as the Job-Shop Scheduling Problem (JSP) and Knapsack Problem (KP) are fundamental challenges in operations re...
Related: #Technology, #Deep Learning -
🇺🇸 OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling
[USA]
arXiv:2601.19924v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated impressive progress in optimization modeling, fostering a rapid expansion of new methodologies and eva...
Related: #Technology, #Benchmarking