4 Search Results for "Hua, Qi Cheng"

Document
DOI: 10.4230/LIPIcs.TIME.2024.17
Time Series Anomaly Detection Leveraging MSE Feedback with AutoEncoder and RNN

Authors: Ibrahim Delibasoglu and Fredrik Heintz

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

Abstract
Anomaly detection in time series data is a critical task in various domains, including finance, healthcare, cybersecurity and industry. Traditional methods, such as time series decomposition, clustering, and density estimation, have provided robust solutions for identifying anomalies that exhibit distinct patterns or significant deviations from normal data distributions. Recent advancements in machine learning and deep learning have further enhanced these capabilities. This paper introduces a novel method for anomaly detection that combines the strengths of autoencoders and recurrent neural networks (RNNs) with an reconstruction error feedback mechanism based on Mean Squared Error. We compare our method against classical techniques and recent approaches like OmniAnomaly, which leverages stochastic recurrent neural networks, and the Anomaly Transformer, which introduces association discrepancy to capture long-range dependencies and DCDetector using contrastive representation learning with multi-scale dual attention. Experimental results demonstrate that our method achieves superior overall performance in terms of precision, recall, and F1 score. The source code is available at http://github.com/mribrahim/AE-FAR
Cite as

Ibrahim Delibasoglu and Fredrik Heintz. Time Series Anomaly Detection Leveraging MSE Feedback with AutoEncoder and RNN. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 17:1-17:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{delibasoglu_et_al:LIPIcs.TIME.2024.17,
  author =	{Delibasoglu, Ibrahim and Heintz, Fredrik},
  title =	{{Time Series Anomaly Detection Leveraging MSE Feedback with AutoEncoder and RNN}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{17:1--17:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.17},
  URN =		{urn:nbn:de:0030-drops-212244},
  doi =		{10.4230/LIPIcs.TIME.2024.17},
  annote =	{Keywords: Time series, Anomaly, Neural networks}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2024.22
Scheduling Splittable Jobs on Configurable Machines

Authors: Matthew Casey, Rajmohan Rajaraman, David Stalfa, and Cheng Tan

Published in: LIPIcs, Volume 317, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)

Abstract
Motivated by modern architectures allowing for the partitioning of a GPU into hardware separated instances, we initiate the study of scheduling splittable jobs on configurable machines. We consider machines that can be configured into smaller instances, which we call blocks, in multiple ways, each of which is referred to as a configuration. We introduce the Configurable Machine Scheduling (cms) problem, where we are given n jobs and a set C of configurations. A schedule consists of a set of machines, each assigned some configuration in C with each block in the configuration assigned to process one job. The amount of a job’s demand that is satisfied by a block is given by an arbitrary function of the job and block. The objective is to construct a schedule using as few machines as possible. We provide a tight logarithmic factor approximation algorithm for this problem in the general setting, a factor (3 + ε) approximation algorithm for arbitrary ε > 0 when there are O(1) input configurations, and a polynomial time approximation scheme when both the number and size of configurations are O(1). Finally, we utilize a technique for finding conic integer combinations in fixed dimension to develop an optimal polynomial time algorithm in the case with O(1) jobs, O(1) blocks, and every configuration up to a given size.
Cite as

Matthew Casey, Rajmohan Rajaraman, David Stalfa, and Cheng Tan. Scheduling Splittable Jobs on Configurable Machines. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 22:1-22:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{casey_et_al:LIPIcs.APPROX/RANDOM.2024.22,
  author =	{Casey, Matthew and Rajaraman, Rajmohan and Stalfa, David and Tan, Cheng},
  title =	{{Scheduling Splittable Jobs on Configurable Machines}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{22:1--22:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-348-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{317},
  editor =	{Kumar, Amit and Ron-Zewi, Noga},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2024.22},
  URN =		{urn:nbn:de:0030-drops-210157},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.22},
  annote =	{Keywords: Scheduling algorithms, Approximation algorithms, Configurable machines, Splittable jobs, Linear programming}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2024.7
The Omnivisor: A Real-Time Static Partitioning Hypervisor Extension for Heterogeneous Core Virtualization over MPSoCs

Authors: Daniele Ottaviano, Francesco Ciraolo, Renato Mancuso, and Marcello Cinque

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract
Following the needs of industrial applications, virtualization has emerged as one of the most effective approaches for the consolidation of mixed-criticality systems while meeting tight constraints in terms of space, weight, power, and cost (SWaP-C). In embedded platforms with homogeneous processors, a wealth of works have proposed designs and techniques to enforce spatio-temporal isolation by leveraging well-understood virtualization support. Unfortunately, achieving the same goal on heterogeneous MultiProcessor Systems-on-Chip (MPSoCs) has been largely overlooked. Modern hypervisors are designed to operate exclusively on main cores, with little or no consideration given to other co-processors within the system, such as small microcontroller-level CPUs or soft-cores deployed on programmable logic (FPGA). Typically, hypervisors consider co-processors as I/O devices allocated to virtual machines that run on primary cores, yielding full control and responsibility over them. Nevertheless, inadequate management of these resources can lead to spatio-temporal isolation issues within the system. In this paper, we propose the Omnivisor model as a paradigm for the holistic management of heterogeneous platforms. The model generalizes the features of real-time static partitioning hypervisors to enable the execution of virtual machines on processors with different Instruction Set Architectures (ISAs) within the same MPSoC. Moreover, the Omnivisor ensures temporal and spatial isolation between virtual machines by integrating and leveraging a variety of hardware and software protection mechanisms. The presented approach not only expands the scope of virtualization in MPSoCs but also enhances the overall system reliability and real-time performance for mixed-criticality applications. A full open-source reference implementation of the Omnivisor based on the Jailhouse hypervisor is provided, targeting ARM real-time processing units and RISC-V soft-cores on FPGA. Experimental results on real hardware show the benefits of the solution, including enabling the seamless launch of virtual machines on different ISAs and extending spatial/temporal isolation to heterogenous cores with enhanced regulation policies.
Cite as

Daniele Ottaviano, Francesco Ciraolo, Renato Mancuso, and Marcello Cinque. The Omnivisor: A Real-Time Static Partitioning Hypervisor Extension for Heterogeneous Core Virtualization over MPSoCs. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 7:1-7:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{ottaviano_et_al:LIPIcs.ECRTS.2024.7,
  author =	{Ottaviano, Daniele and Ciraolo, Francesco and Mancuso, Renato and Cinque, Marcello},
  title =	{{The Omnivisor: A Real-Time Static Partitioning Hypervisor Extension for Heterogeneous Core Virtualization over MPSoCs}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{7:1--7:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.7},
  URN =		{urn:nbn:de:0030-drops-203107},
  doi =		{10.4230/LIPIcs.ECRTS.2024.7},
  annote =	{Keywords: Mixed-Criticality, Embedded Virtualization, Real-Time Systems, MPSoCs}
}
Document
DOI: 10.4230/LIPIcs.SAND.2022.18
Fully Dynamic Four-Vertex Subgraph Counting

Authors: Kathrin Hanauer, Monika Henzinger, and Qi Cheng Hua

Published in: LIPIcs, Volume 221, 1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022)

Abstract
This paper presents a comprehensive study of algorithms for maintaining the number of all connected four-vertex subgraphs in a dynamic graph. Specifically, our algorithms maintain the number of paths of length three in deterministic amortized O(m^{1/2}) update time, and any other connected four-vertex subgraph which is not a clique in deterministic amortized update time O(m^{2/3}). Queries can be answered in constant time. We also study the query times for subgraphs containing an arbitrary edge that is supplied only with the query as well as the case where only subgraphs containing a vertex s that is fixed beforehand are considered. For length-3 paths, paws, 4-cycles, and diamonds our bounds match or are not far from (conditional) lower bounds: Based on the OMv conjecture we show that any dynamic algorithm that detects the existence of paws, diamonds, or 4-cycles or that counts length-3 paths takes update time Ω(m^{1/2-δ}). Additionally, for 4-cliques and all connected induced subgraphs, we show a lower bound of Ω(m^{1-δ}) for any small constant δ > 0 for the amortized update time, assuming the static combinatorial 4-clique conjecture holds. This shows that the O(m) algorithm by Eppstein et al. [David Eppstein et al., 2012] for these subgraphs cannot be improved by a polynomial factor.
Cite as

Kathrin Hanauer, Monika Henzinger, and Qi Cheng Hua. Fully Dynamic Four-Vertex Subgraph Counting. In 1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 221, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{hanauer_et_al:LIPIcs.SAND.2022.18,
  author =	{Hanauer, Kathrin and Henzinger, Monika and Hua, Qi Cheng},
  title =	{{Fully Dynamic Four-Vertex Subgraph Counting}},
  booktitle =	{1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022)},
  pages =	{18:1--18:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-224-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{221},
  editor =	{Aspnes, James and Michail, Othon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAND.2022.18},
  URN =		{urn:nbn:de:0030-drops-159608},
  doi =		{10.4230/LIPIcs.SAND.2022.18},
  annote =	{Keywords: Dynamic Graph Algorithms, Subgraph Counting, Motif Search}
}
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