no code implementations • 27 Mar 2024 • Huy Q. Ngo, Mingyu Guo, Hung Nguyen
We proposed a novel metric called response time, to measure the effectiveness of our decoy placement in temporal attack graphs.
no code implementations • 15 Feb 2024 • Ravi Hammond, Dustin Craggs, Mingyu Guo, Jakob Foerster, Ian Reid
In many collaborative settings, artificial intelligence (AI) agents must be able to adapt to new teammates that use unknown or previously unobserved strategies.
no code implementations • 15 Jan 2024 • Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann
Creating diverse sets of high quality solutions has become an important problem in recent years.
no code implementations • 28 Dec 2023 • Huy Quang Ngo, Mingyu Guo, Hung Nguyen
To solve the dynamic graph problem, we re-design the mixed-integer programming formulation by combining m MIP (dyMIP(m)) instances to produce a near-optimal blocking plan.
no code implementations • 11 Dec 2023 • Sangwon Hyun, Mingyu Guo, M. Ali Babar
Through the experiments conducted with three prominent LLMs, we have confirmed that the METAL framework effectively evaluates essential QAs on primary LLM tasks and reveals the quality risks in LLMs.
1 code implementation • 3 Oct 2023 • Nam Trong Dinh, Sahand Karimi-Arpanahi, S. Ali Pourmousavi, Mingyu Guo, Julian Lemos-Vinasco, Jon A. R. Liisberg
In this paper, we compare the most common existing sizing methods in the literature with a battery sizing model that incorporates the practical operation of a battery, that is, receding horizon operation.
no code implementations • 16 Sep 2023 • Nam Trong Dinh, Sahand Karimi-Arpanahi, Rui Yuan, S. Ali Pourmousavi, Mingyu Guo, Jon A. R. Liisberg, Julian Lemos-Vinasco
Demand response (DR) plays a critical role in ensuring efficient electricity consumption and optimal use of network assets.
no code implementations • 8 Apr 2023 • Diksha Goel, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo
The defender picks a specific environment configuration.
no code implementations • 25 Feb 2023 • Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen
Given a source s and a destination t, we aim to test s-t connectivity by identifying either a path (consisting of only On edges) or a cut (consisting of only Off edges).
no code implementations • 27 Jul 2022 • Jianshu Li, Man Luo, Jian Liu, Tao Chen, Chengjie Wang, Ziwei Liu, Shuo Liu, Kewei Yang, Xuning Shao, Kang Chen, Boyuan Liu, Mingyu Guo, Ying Guo, Yingying Ao, Pengfei Gao
In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
no code implementations • 7 Apr 2022 • Diksha Goel, Max Ward, Aneta Neumann, Frank Neumann, Hung Nguyen, Mingyu Guo
We show that the problem is #P-hard and, therefore, intractable to solve exactly.
1 code implementation • 25 Jan 2022 • Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann
In this work, we consider the problem of finding a set of tours to a traveling salesperson problem (TSP) instance maximizing diversity, while satisfying a given cost constraint.
no code implementations • 25 Dec 2021 • Mingyu Guo, Jialiang Li, Aneta Neumann, Frank Neumann, Hung Nguyen
The other assumes a small number of splitting nodes (nodes with multiple out-going edges).
no code implementations • 23 Sep 2021 • Congbo Ma, Wei Emma Zhang, Hu Wang, Shubham Gupta, Mingyu Guo
In this work, we develop a neural network based model which leverages dependency parsing to capture cross-positional dependencies and grammatical structures.
1 code implementation • 25 Feb 2021 • Yuanhan Zhang, Zhenfei Yin, Jing Shao, Ziwei Liu, Shuo Yang, Yuanjun Xiong, Wei Xia, Yan Xu, Man Luo, Jian Liu, Jianshu Li, Zhijun Chen, Mingyu Guo, Hui Li, Junfu Liu, Pengfei Gao, Tianqi Hong, Hao Han, Shijie Liu, Xinhua Chen, Di Qiu, Cheng Zhen, Dashuang Liang, Yufeng Jin, Zhanlong Hao
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
no code implementations • 23 Feb 2021 • Anh Viet Do, Mingyu Guo, Aneta Neumann, Frank Neumann
This work contributes to this line of research with an investigation on evolutionary diversity optimization for three of the most well-studied permutation problems, namely the Traveling Salesperson Problem (TSP), both symmetric and asymmetric variants, and Quadratic Assignment Problem (QAP).
no code implementations • 10 Nov 2020 • Congbo Ma, Wei Emma Zhang, Mingyu Guo, Hu Wang, Quan Z. Sheng
Multi-document summarization (MDS) is an effective tool for information aggregation that generates an informative and concise summary from a cluster of topic-related documents.