Cooperative Multi-Agent Reinforcement Learning via Epigraph-Form Guided Exploration
arXiv:2611.07066v1 Announce Type: cross Abstract: Discovering cooperative behavior in multi-agent reinforcement learning (MARL) is challenging due to the combin…
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arXiv:2611.07066v1 Announce Type: cross Abstract: Discovering cooperative behavior in multi-agent reinforcement learning (MARL) is challenging due to the combin…
arXiv:2611.08312v1 Announce Type: new Abstract: Personal AI agents often act on underspecified instructions and draw on context such as their user's messages an…
arXiv:2611.07377v1 Announce Type: new Abstract: Generative video models have made video creation more accessible, yet creators still struggle to translate high-…
arXiv:2611.07374v1 Announce Type: new Abstract: Driven by the rapid development of the low-altitude economy, Uncrewed Aerial Vehicle (UAV) networks have become …
arXiv:2611.07140v1 Announce Type: new Abstract: Teams increasingly build software from cooperating large language model (LLM) agents, often assuming more agents…
arXiv:2611.07050v1 Announce Type: new Abstract: Delegated Agent2Agent (A2A) workflows create a security problem when the agent sending a request is different fr…
arXiv:2611.04612v2 Announce Type: replace-cross Abstract: Distributed statistical learning has recently attracted significant attention owing to its computation…
arXiv:2609.30565v2 Announce Type: replace-cross Abstract: Many real-world high-dimensional time series exhibit long-memory, but Gaussian graphical model testing…
arXiv:2609.20260v2 Announce Type: replace-cross Abstract: We comment on the optimally-transported generalized method of moments (OTGMM) of Schennach and Starck …
arXiv:2608.22608v2 Announce Type: replace-cross Abstract: During clinical trials evaluating a drug's effect on a survival endpoint, intermediate events often oc…
arXiv:2605.10842v3 Announce Type: replace-cross Abstract: We construct moment functions that are Neyman-orthogonal to a chosen order in moment-condition models …
arXiv:2605.09214v2 Announce Type: replace-cross Abstract: \emph{Kullback-Leibler} (KL) regularization is ubiquitous in reinforcement learning algorithms in the …
arXiv:2604.26942v2 Announce Type: replace-cross Abstract: We introduce Hyper Input Convex Neural Networks (HyCNNs), a novel neural network architecture designed…
arXiv:2511.03087v3 Announce Type: replace-cross Abstract: Generalized linear models (GLMs) are fundamental tools for statistical modeling, with maximum likeliho…
arXiv:2608.01364v4 Announce Type: replace Abstract: Unbiased squared distance covariance and the Hilbert-Schmidt independence criterion (HSIC) are fourth-order …
arXiv:2606.06018v2 Announce Type: replace Abstract: We consider a periodic scalar reaction-diffusion system over a two-dimensional domain under natural conditio…
arXiv:2605.31416v3 Announce Type: replace Abstract: Fractional Gaussian noise and $\FARIMA(0,d,0)$ have the same long-memory pole $|\theta|^{-2d}$ and hence the…
arXiv:2512.24669v2 Announce Type: replace Abstract: Contextual bandits are a central framework for sequential decision-making, with applications ranging from re…
arXiv:2510.17561v2 Announce Type: replace Abstract: We provide a rigorous random matrix theory analysis of spiked cross-covariance models where the signals acro…
arXiv:2611.06987v1 Announce Type: cross Abstract: The Behrens--Fisher fiducial interval for the difference of two normal means is known from the numerical work …