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Randomization in the two-parameter optimal stopping problem
Related publications (119)
The connection of the acyclic disconnection and feedback arc sets - On an open problem of Figueroa et al.
We examine the connection of two graph parameters, the size of a minimum feedback arcs set and the acyclic disconnection. A feedback arc set of a directed graph is a subset of arcs such that after deletion the graph becomes acyclic. The acyclic disconnecti ...
Elsevier2024Graph Exploration for Effective Multiagent Q-Learning
This article proposes an exploration technique for multiagent reinforcement learning (MARL) with graph-based communication among agents. We assume that the individual rewards received by the agents are independent of the actions by the other agents, while ...
Ieee-Inst Electrical Electronics Engineers Inc2024An extension of the stochastic sewing lemma and applications to fractional stochastic calculus
We give an extension of Le's stochastic sewing lemma. The stochastic sewing lemma proves convergence in of Riemann type sums for an adapted two-parameter stochastic process A, under certain conditions on the moments o ...
Cambridge Univ Press2024Multiscale pattern analysis of building replacements in Zurich from 2000 to 2019
Corentin Jean Dominique Fivet, Jingxian Ye
Building replacement (BR) – i.e., the demolition of existing structures and subsequent construction of new buildings on the same site – is often understood as a necessary urban planning strategy despite significant environmental implications regarding soli ...
2023Metastability of the Potts Ferromagnet on Random Regular Graphs
We study the performance of Markov chains for the q-state ferromagnetic Potts model on random regular graphs. While the cases of the grid and the complete graph are by now well-understood, the case of random regular graphs has resisted a detailed analysis ...
SPRINGER2023Scalable maximal subgraph mining with backbone-preserving graph convolutions
Karl Aberer, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên
Maximal subgraph mining is increasingly important in various domains, including bioinformatics, genomics, and chemistry, as it helps identify common characteristics among a set of graphs and enables their classification into different categories. Existing ...
ELSEVIER SCIENCE INC2023Stochastic homogenization of degenerate integral functionals with linear growth
We study the limit behaviour of sequences of non-convex, vectorial, random integral functionals, defined on W1,1, whose integrands are ergodic and satisfy degenerate linear growth conditions. The latter involve suitable random, scale-dependent weight-funct ...
2023Unambiguous DNFs and Alon-Saks-Seymour
Mika Tapani Göös, Siddhartha Jain
We exhibit an unambiguous k-DNF formula that requires CNF width (Omega) over tilde (k(2)), which is optimal up to logarithmic factors. As a consequence, we get a near-optimal solution to the Alon-Saks-Seymour problem in graph theory (posed in 1991), which ...
IEEE COMPUTER SOC2022fGOT: Graph Distances Based on Filters and Optimal Transport
Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic, Giovanni Chierchia
Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022Graph Neural Networks With Lifting-Based Adaptive Graph Wavelets
Pascal Frossard, Chenglin Li, Mingxing Xu
Spectral-based graph neural networks (SGNNs) have been attracting increasing attention in graph representation learning. However, existing SGNNs are limited in implementing graph filters with rigid transforms and cannot adapt to signals residing on graphs ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022