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Related Articles from SNS
Multi-Objective Submodular Maximization with Differential Privacy
arXiv:2606.05596v1 Announce Type: new Abstract: In this paper, we study multi-objective submodular maximization (MOSM) subject to a cardinality constraint under differential privacy (DP). Specifically, we aim to select a set of at most $k \in \mathbb{Z}_{+}$ elements to maximize the minimum of $d > 1$ monotone submodular functions while satisfying $\varepsilon$-DP. Although extensive studies have been conducted on both differentially private single-objective submodular maximization on...
Algorithmically Fair Maximization of Multiple Submodular Objective Functions and Implications to Constrained Fair Division
Announce Type: replace Abstract: Constrained maximization of submodular functions is a central problem in combinatorial optimization. In many realistic scenarios, multiple agents each need to maximize their own submodular objective over a common ground set, subject to individual constraints, with the requirement that their solutions be disjoint. We study this setting through the lens of algorithmic fairness and constrained fair division.
On the Maximal Length of MDS Elliptic Codes
arXiv:2605.29439v2 Announce Type: replace Abstract: The determination of the maximal length of maximum distance separable (MDS) codes arising from elliptic curves is a central problem in coding theory. For an elliptic curve $E$ over $\mathbb{F}_q$, let $\operatorname{MEC}(k,q)$ denote the maximal length of a $q$-ary MDS elliptic code of dimension $k$. It was recently shown that $\operatorname{MEC}(k,q)\le\frac{q+1}{2}+\sqrt{q}$ for $q\ge289$ and $3\le k\le(q+1-2\sqrt{q})/10$, with equality...
Coherence Maximization Improves Pluralistic Alignment
arXiv:2606.03110v2 Announce Type: replace Abstract: Aligning AI systems with diverse human values requires value specifications grounded in concrete examples, but generating such examples without extensive human supervision remains an open challenge. We investigate what makes these examples effective, using Internal Coherence Maximization (ICM) -- which infers labels by maximizing their mutual predictability -- to generate persona-specific examples that steer a model toward a target group's...
Coherence Maximization Improves Pluralistic Alignment
arXiv:2606.03110v1 Announce Type: new Abstract: Aligning AI systems with diverse human values requires value specifications grounded in concrete examples, but generating such examples without extensive human supervision remains an open challenge. We investigate what makes these examples effective, using Internal Coherence Maximization (ICM) -- which infers labels by maximizing their mutual predictability -- to generate persona-specific examples that steer a model toward a target group's...
Welfare Maximization in Bilateral Trade: Improved Approximation Guarantees Beyond the Fixed Price Barrier
Announce Type: new Abstract: We study the setting of welfare maximization in bilateral trade, where the values of both the buyer and the seller are drawn from independent distributions. Our goal is to maximize social welfare. In this setting, fixed price mechanisms have been extensively studied.
Optimal Feedback Communication with Information Maximization and Distortion Minimization
Announce Type: new Abstract: We study the problem of optimally sending a real-valued source through multiple uses of a channel with feedback. First, we state a set of conditions that are sufficient for an encoder to achieve maximal mutual information between the source and all the channel outputs. This set of conditions are also necessary when the channel is input-identifiable, a condition widely satisfied by common channel models.
Scaling Higher-Order Graph Learning with Maximal Clique Complexes
arXiv:2605.31373v1 Announce Type: new Abstract: Graph neural networks (GNNs) are limited to modeling pairwise interactions, while higher-order models based on cell complexes achieve greater expressivity but often suffer from poor scalability. We introduce simplified and factored cellular Weisfeiler Leman tests (sCWL and fCWL), which preserve the expressivity of the CWL test while improving computational efficiency. We further introduce the maximal clique complex, enabling scalable CWNs with...
Managing hydrogen emissions is key to maximizing climate benefits as hydrogen use expands, say researchers
Managing hydrogen emissions is key to maximizing climate benefits as hydrogen use expands, say researchers Lisa Lock Scientific Editor Robert Egan Associate Editor Current estimates of hydrogen's climate impact are now sufficiently robust to inform policy and business decision-making, according to researchers in a new review article on the climate impacts of hydrogen emissions. Hydrogen is expected to be an important component of future low-carbon energy and industrial systems, particularly...
DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming
Announce Type: new Abstract: Next-generation wireless networks, including satellite-to-Open RAN systems, demand agile and intelligent resource management capable of handling dynamic multi-user interference under stochastic quality of service constraints. This paper introduces DIFFRACT, a neuralized utility maximization framework that leverages differentiable programming to integrate deep learning with optimization in wireless networks. Central to our approach is the exploitation of the...