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We study the power of multiple choices in online stochastic matching. Despite a long line of research, existing algorithms still only consider two choices of offline neighbors for each online vertex because of the technical challenge in…

Data Structures and Algorithms · Computer Science 2022-03-08 Zhiyi Huang , Xinkai Shu , Shuyi Yan

Bayesian persuasion is a model for understanding strategic information revelation: an agent with an informational advantage, called a sender, strategically discloses information by sending signals to another agent, called a receiver. In…

Computer Science and Game Theory · Computer Science 2021-12-14 Kaito Fujii , Shinsaku Sakaue

We propose multi-type probabilistic serial (MPS) and multi-type random priority (MRP) as extensions of the well known PS and RP mechanisms to the multi-type resource allocation problem (MTRA) with partial preferences. In our setting, there…

Artificial Intelligence · Computer Science 2020-10-30 Haibin Wang , Sujoy Sikdar , Xiaoxi Guo , Lirong Xia , Yongzhi Cao , Hanpin Wang

Given vectors $v_1,\dots,v_n\in\mathbb{R}^d$ and a matroid $M=([n],I)$, we study the problem of finding a basis $S$ of $M$ such that $\det(\sum_{i \in S}v_i v_i^\top)$ is maximized. This problem appears in a diverse set of areas such as…

Data Structures and Algorithms · Computer Science 2020-04-20 Vivek Madan , Aleksandar Nikolov , Mohit Singh , Uthaipon Tantipongpipat

We study various generalizations of the secretary problem with submodular objective functions. Generally, a set of requests is revealed step-by-step to an algorithm in random order. For each request, one option has to be selected so as to…

Data Structures and Algorithms · Computer Science 2016-08-01 Thomas Kesselheim , Andreas Tönnis

In this article, we investigate the multi-parametric matroid problem. The weights of the elements of the matroid's ground set depend linearly on an arbitrary but fixed number of parameters, each of which is taken from a real interval. The…

Combinatorics · Mathematics 2025-03-13 Nils Hausbrandt , Stefan Ruzika

We present an efficient algorithm to solve semirandom planted instances of any Boolean constraint satisfaction problem (CSP). The semirandom model is a hybrid between worst-case and average-case input models, where the input is generated by…

Computational Complexity · Computer Science 2023-10-02 Venkatesan Guruswami , Jun-Ting Hsieh , Pravesh K. Kothari , Peter Manohar

The random-order or secretary model is one of the most popular beyond-worst case model for online algorithms. While it avoids the pessimism of the traditional adversarial model, in practice we cannot expect the input to be presented in…

Data Structures and Algorithms · Computer Science 2020-06-23 Thomas Kesselheim , Marco Molinaro

We provide a simple $(1-O(\frac{1}{\sqrt{k}}))$-selectable Online Contention Resolution Scheme for $k$-uniform matroids against a fixed-order adversary. If $A_i$ and $G_i$ denote the set of selected elements and the set of realized active…

Data Structures and Algorithms · Computer Science 2023-11-28 Atanas Dinev , S. Matthew Weinberg

In this study, we consider a class of linear matroid interdiction problems, where the feasible sets for the upper-level decision-maker (referred to as a leader) and the lower-level decision-maker (referred to as a follower) are induced by…

Computational Complexity · Computer Science 2025-08-26 Sergey S. Ketkov , Oleg A. Prokopyev

Within the context of stochastic probing with commitment, we consider the online stochastic matching problem; that is, the one sided online bipartite matching problem where edges adjacent to an online node must be probed to determine if…

Data Structures and Algorithms · Computer Science 2021-01-07 Allan Borodin , Calum MacRury , Akash Rakheja

We study the problem of solving Packing Integer Programs (PIPs) in the online setting, where columns in $[0,1]^d$ of the constraint matrix are revealed sequentially, and the goal is to pick a subset of the columns that sum to at most $B$ in…

Data Structures and Algorithms · Computer Science 2021-12-28 C. J. Argue , Anupam Gupta , Marco Molinaro , Sahil Singla

Severe impossibility results restrict the design of strategyproof random assignment mechanisms, and trade-offs are necessary when aiming for more demanding efficiency requirements, such as ordinal or rank efficiency. We introduce hybrid…

Computer Science and Game Theory · Computer Science 2017-07-11 Timo Mennle , Sven Seuken

Milgrom (2017) has proposed a heuristic for determining a maximum weight basis of an independence system ${\mathcal I}$ given that we want an approximation guarantee only for sets in a prescribed ${\mathcal O}\subseteq {\mathcal I}$. This…

Discrete Mathematics · Computer Science 2020-04-08 Sven de Vries , Rakesh V. Vohra

We study the problem of allocating indivisible goods among strategic agents. We focus on settings wherein monetary transfers are not available and each agent's private valuation is a submodular function with binary marginals, i.e., the…

Computer Science and Game Theory · Computer Science 2021-09-14 Siddharth Barman , Paritosh Verma

Querying complex models for precise information (e.g. traffic models, database systems, large ML models) often entails intense computations and results in long response times. Thus, weaker models which give imprecise results quickly can be…

Data Structures and Algorithms · Computer Science 2024-11-06 Franziska Eberle , Felix Hommelsheim , Alexander Lindermayr , Zhenwei Liu , Nicole Megow , Jens Schlöter

We investigate the power of randomized algorithms for the maximum cardinality matching (MCM) and the maximum weight matching (MWM) problems in the online preemptive model. In this model, the edges of a graph are revealed one by one and the…

Data Structures and Algorithms · Computer Science 2015-07-03 Ashish Chiplunkar , Sumedh Tirodkar , Sundar Vishwanathan

In this paper, we investigate the online parcel assignment (OPA) problem, in which each stochastically generated parcel needs to be assigned to a candidate route for delivery to minimize the total cost subject to certain business…

Machine Learning · Computer Science 2023-01-18 Hao Zeng , Qiong Wu , Kunpeng Han , Junying He , Haoyuan Hu

We study an online version of the max-min fair allocation problem for indivisible items. In this problem, items arrive one by one, and each item must be allocated irrevocably on arrival to one of $n$ agents, who have additive valuations for…

Computer Science and Game Theory · Computer Science 2021-11-16 Yasushi Kawase , Hanna Sumita

We study the online metric matching problem. There are $m$ servers and $n$ requests located in a metric space, where all servers are available upfront and requests arrive one at a time. Upon the arrival of a new request, it needs to be…

Data Structures and Algorithms · Computer Science 2025-10-16 Mingwei Yang , Sophie H. Yu
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