arXiv Machine Learning
Jun 2
Towards Optimal Robustness in Learning-Augmented Paging
arXiv:2606. 01342v1 Announce Type: cross Abstract: Learning-augmented paging has been extensively studied in recent years.
Learning-Augmented Online Minimization with Dual Predictions
arXiv:2606. 05380v1 Announce Type: cross Abstract: We present learning-augmented algorithms for two general classes of online minimization problems: metrical task systems and laminar set cover.
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arXiv Machine Learning
Aug 4
Learning-Based Stochastic Optimal Control with Infinite-Horizon Probabilistic Constraints
arXiv:2608. 01151v1 Announce Type: cross Abstract: In this paper, we consider stochastic optimal control problems with infinite-horizon joint chance constraints.
arXiv Machine Learning
Jul 31
Learning-Augmented Algorithms for Online Vertex Cover
arXiv:2606. 22831v2 Announce Type: replace-cross Abstract: This paper studies learning-augmented online weighted vertex cover with local advice and a tradeoff parameter $\lambda \in (0,1)$.
Hugging Face Trending Papers
Jun 11
Learning-Augmented Approximation for Unrelated-Machines Makespan Scheduling
Recently, Antoniadis et al. (ICLR 2025) proposed a framework for incorporating predictions to approximate NP-hard selection problems.
arXiv Machine Learning
Sep 10
A First-Order Learning Algorithm for Online Resource Allocation with Constant Regret
arXiv:2609.05895v1 Announce Type: new Abstract: We study a finite-horizon online resource allocation problem with initial resource capacities proportional to the horizon. In each period, a request ty...
arXiv Machine Learning
Jun 2
Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts
arXiv:2605. 09382v2 Announce Type: replace Abstract: The Linear Assignment Problem is a fundamental combinatorial optimization task where classical exact solvers ensure optimality but suffer from an $\mathcal{O}(N^{3})$ bottleneck, while recent neural approximations struggle with scalability and exactness.
arXiv Machine Learning
Sep 21
Offline Constrained RLHF with Multiple Preference Oracles
arXiv:2604.00200v2 Announce Type: replace Abstract: We study offline constrained reinforcement learning from human feedback with multiple preference oracles. Motivated by applications that trade off...
arXiv Machine Learning
Sep 24
Tight Regret Bound for Online Inverse Linear Optimization via Multiscale Matrix Weights
arXiv:2609. 26978v1 Announce Type: cross Abstract: We study online inverse linear optimization with a fixed unknown linear utility: in each round, an environment presents a compact action set, the learner recommends an action from it, and the environment returns an action that maximizes the utility over the same set.
arXiv Machine Learning
Jun 4
Offline-to-Online Learning in Linear Bandits
arXiv:2606. 04305v1 Announce Type: new Abstract: We study online learning with an additional offline dataset in the stochastic linear bandit setting.
arXiv Statistics ML
2d ago
The Curvature of Regret in Contextual Linear Optimization
arXiv:2610.01980v1 Announce Type: cross Abstract: Decision-focused learning for linear optimization is complicated by the discontinuity of the optimizer, where small cost errors may leave the decisio...
arXiv Machine Learning
Jul 27
Fast State-Augmented Learning for Wireless Resource Allocation with Dual Variable Regression
arXiv:2506. 18748v2 Announce Type: replace-cross Abstract: We consider resource allocation problems in multi-user wireless networks, where the goal is to optimize a network-wide utility function subject to constraints on the ergodic average performance of users.
arXiv Machine Learning
Jun 2
Distributed GNEP Algorithms without Multiplier Sharing and Applications to Multi-Robot Coordination and Contextual Bandit-Based Active Learning
arXiv:2606. 00759v1 Announce Type: new Abstract: Recent advances in artificial intelligence have expanded the focus from classical optimization to include equilibrium analysis in noncooperative games.