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The main focus of this article is radius-based (supplier) clustering in the two-stage stochastic setting with recourse, where the inherent stochasticity of the model comes in the form of a budget constraint. In addition to the standard (homogeneous) ...

In a game of persuasion with evidence, a sender has private information. By presenting evidence on the information, the sender wishes to persuade a receiver to take a single action (e.g., hire a job candidate, or convict a defendant). The sender’s utility ...

Submodular function optimization is a fundamental tool in modeling complex interactions in machine learning and graph mining problems. We propose to study constrained submodular optimization to improve the current state of the art. Our goals are to ...

This paper delves into the interpretability of Graph Neural Networks in the context of Boolean Satisfiability. The goal is to demystify the internal workings of these models and provide insightful perspectives into their decision-making processes. This ...

Submodular optimization finds applications in machine learning and data mining. In this paper, we study the problem of maximizing functions of the form h = f-c, where f is a monotone, non-negative, weakly submodular set function and c is a modular ...

This is an annotated reading list on research towards designing socially efficient mechanisms for bilateral trade and its generalizations.

Given a social network G, a cost associated with each user, and an influence threshold η, the minimum cost seed selection problem (MCSS) aims to find a set of seeds that minimizes the total cost to reach η users. Existing works are mainly devoted to ...

PageRank is a commonly used measurement in a wide range of applications, including search engines, recommendation systems, and social networks. However, this measurement suffers from huge computational overhead, which cannot be scaled to large graphs. ...

This paper studies the parity-constrained weighted k-center (PARW k-center) problem. In the PARW k-center problem, we are given a set of vertices in a metric space with distances and a non-negative budget k. Additionally, each vertex is associated ...

Taking a good decision about the assignment of each job becomes crucial in the era of hybrid and heterogeneous computing systems, such as personal machines equipped with CPUs and GPUs, or HPC platforms composed of multiple generations of ...$\mathrm{}\mathrm{}\sqrt{\mathrm{}}$$\mathrm{}$$\mathrm{}$

Thebiharmonic distance (BD) is a fundamental metric that measures the distance of two nodes in a graph. It has found applications in network coherence, machine learning, and computational graphics, among others. In spite of BD's importance, efficient ...

The Fréchet distance is a popular measure of dissimilarity for polygonal curves. It is defined as a min–max formulation that considers all orientation-preserving bijective mappings between the two curves. Because of its susceptibility to noise, Driemel ...

Category trees, or taxonomies, are rooted trees where each node, called a category, corresponds to a set of related items. The construction of taxonomies has been studied in various domains, including e-commerce, document management, and question ...

We study auction design within the widely acclaimed model of interdependent values, introduced by Milgrom and Weber [1982]. In this model, every bidder i has a private signal s_i for the item for sale, and a public valuation function υ_i (s₁, ..., s_n) ...

We settle the pseudo-polynomial complexity of the Demand Strip Packing (DSP) problem: Given a strip of fixed width and a set of items with widths and heights, the items must be placed inside the strip with the objective of minimizing the peak height. ...

Currently, the best known tradeoff between approximation ratio and complexity for the Sparsest Cut problem is achieved by the algorithm in [Sherman, FOCS 2009]: it computes O(√(log n)/ε)-approximation using O(n^ε log^O(1) n) maxflows for any ε∈[Θ(1/log n),...

We study algorithms for estimating the size of maximum matching. This problem has been subject to extensive research. For n-vertex graphs, Bhattacharya, Kiss, and Saranurak [FOCS’23] (BKS) showed that an estimate that is within є n of the optimal ...

In the classic Correlation Clustering problem introduced by Bansal, Blum, and Chawla ‍(FOCS 2002), the input is a complete graph where edges are labeled either + or −, and the goal is to find a partition of the vertices that minimizes the sum of the +...

While the search for quantum advantage typically focuses on speed­ups in execution time, quantum algorithms also offer the potential for advantage in space complexity. Previous work has shown such advantages for data stream problems, in which elements ...

Scheduling packets with end-to-end deadline constraints in multihop networks is an important problem that has been notoriously difficult to tackle. Recently, there has been progress on this problem in the worst-case traffic setting, with the objective of ...