arXiv Machine Learning
Jun 3
Coherent Swap Regret and Channel-Proof Learning
arXiv:2606. 02655v1 Announce Type: cross Abstract: External regret certifies stability only against replacing one's behavior by a fixed alternative.
Average-and Last-Iterate Lower Bounds for Optimistic Matrix Mirror-Prox in Quantum Zero-Sum Games
Related stories
arXiv Machine Learning
1d ago
Fully Online Decentralized Learning in Stochastic Games with Unknown Independent Chains
arXiv:2610. 01181v1 Announce Type: new Abstract: We consider stochastic games with independent controlled chains and unknown transition kernels, where players observe only their local states and realized payoffs.
arXiv Machine Learning
Aug 6
Sublogarithmic Swap Regret in Multiplayer General-Sum Games via Hybrid Regularization
arXiv:2608. 04149v1 Announce Type: cross Abstract: Swap regret governs the rate at which uncoupled learning dynamics converge to correlated equilibria in multiplayer general-sum games.
arXiv Statistics ML
3d ago
Lower Bounds for Linear-Oracle Online Learning
arXiv:2609.38375v1 Announce Type: new Abstract: Can a constant number of linear minimizations per round improve on the $T^{3/4}$ regret rate of online Frank-Wolfe on general convex sets? Weibel et al...
arXiv Machine Learning
Sep 22
A Horizon-Independent Regret Bound for Optimistic Hedge in General-Sum Games
arXiv:2609.22839v1 Announce Type: cross Abstract: Can simple learning rules keep their regret bounded in self-play? Recent work achieves constant regret bounds through modified regularization and hig...
arXiv Machine Learning
Aug 17
Quantum Multi-Armed Bandits and Linear Bandits: Lower Bounds and Algorithms
arXiv:2608. 14319v1 Announce Type: new Abstract: We study quantum multi-armed bandits (QMAB) and quantum linear bandits (QLB) in the model of Wan et al.
arXiv Machine Learning
Aug 26
Optimal Alternating Regret for Online Learning and Games
arXiv:2608.24731v1 Announce Type: new Abstract: We settle the minimax-optimal alternating regret, a regret notion motivated by alternating learning dynamics in games, for both online linear optimizat...
arXiv AI
Jun 29
Which Nash Equilibrium? Solver-Dependent Selection on Zero-Sum Nash Polytopes
arXiv:2606. 28308v1 Announce Type: cross Abstract: Many two-player zero-sum games admit not a unique Nash equilibrium but a convex set of them: a polytope of profiles that all share the minimax value V* yet prescribe different behaviour.
arXiv AI
Sep 2
Independent Reinforcement Learning in Discounted Markov Games
arXiv:2609.00504v1 Announce Type: cross Abstract: In this work, we study radically uncoupled learning in discounted general-sum Markov games. Assuming ``$\mathsf{ETH}$ for $\mathsf{PPAD}$", we show t...
Hugging Face Trending Papers
Jul 2
Optimal Stabilizer Testing and Learning with Limited Quantum Memory
We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-qubit state, but may keep only $k$ qubits of coherent quantum memory between measurements.
arXiv Statistics ML
2d ago
Block Optimism for Nonstationary Bandits with Latent Linear Dynamics
arXiv:2610.00911v1 Announce Type: new Abstract: We study an endogenous nonstationary stochastic bandit problem with latent linear dynamics, where actions affect both immediate rewards and the future...
arXiv Machine Learning
Aug 14
Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry
arXiv:2608. 12753v1 Announce Type: new Abstract: We study decentralized multi-player reinforcement learning in episodic tabular Markov decision processes (MDPs) under three forms of information asymmetry: (A) unobserved actions with common rewards, (B) observed actions with independent rewards, and (C) unobserved actions with independent rewards.