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From the 1 of 12 linked papers with an AI index.

activity
20242026
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12 papers

cs.LG2026

Generalization Bounds on Optimal Control for Transformer Training and Wasserstein Distributional Robustness

Kağan Akman, Naci Saldi, Serdar Yüksel

The paper derives finite‑sample generalization bounds for Transformer models by formulating their training as a finite‑horizon Markovian control problem, using quantized approximat…

math.OC2026

Optimality of Symmetric Independent Policies under Decentralized Mean-Field Information Sharing for Stochastic Teams and Equivalence with McKean-Vlasov Control of a Representative Agent

Sina Sanjari, Naci Saldi, Serdar Yüksel

We study a class of stochastic exchangeable teams with a finite number of decision makers (DMs) as well as their mean-field limits with infinitely many DMs. In the finite populatio…

cs.RO2026

SLAM as a Stochastic Control Problem with Partial Information: Optimal Solutions and Rigorous Approximations

Ilir Gusija, Fady Alajaji, Serdar Yüksel

Simultaneous localization and mapping (SLAM) is a foundational state estimation problem in robotics in which a robot accurately constructs a map of its environment while also local…

math.OC2026

Reinforcement Learning for Jointly Optimal Coding and Control Policies for a Controlled Markovian System over a Communication Channel

Evelyn Hubbard, Liam Cregg, Serdar Yüksel

We study the problem of joint optimization involving coding and control policies for a controlled Markovian sytem over a finite-rate noiseless communication channel. While structur…

cs.LG2026

An Optimal Control Approach To Transformer Training

Kağan Akman, Naci Saldı, Serdar Yüksel

In this paper, we develop a rigorous optimal control-theoretic approach to Transformer training that respects key structural constraints such as (i) realized-input-independence dur…

eess.SY2026

Robustness to Model Approximation, Model Learning From Data, and Sample Complexity in Wasserstein Regular MDPs

Yichen Zhou, Yanglei Song, Serdar Yüksel

The paper studies the robustness properties of discrete-time stochastic optimal control under Wasserstein model approximation for both discounted-cost and average-cost criteria. Sp…