---
_id: '57472'
abstract:
- lang: eng
  text: In this paper we introduce, in a Hilbert space setting, a second order dynamical
    system with asymptotically vanishing damping and vanishing Tikhonov regularization
    that approaches a multiobjective optimization problem with convex and differentiable
    components of the objective function. Trajectory solutions are shown to exist
    in finite dimensions. We prove fast convergence of the function values, quantified
    in terms of a merit function. Based on the regime considered, we establish both
    weak and, in some cases, strong convergence of trajectory solutions toward a weak
    Pareto optimal solution. To achieve this, we apply Tikhonov regularization individually
    to each component of the objective function. This work extends results from single
    objective convex optimization into the multiobjective setting.
author:
- first_name: Radu Ioan
  full_name: Bot, Radu Ioan
  last_name: Bot
- first_name: Konstantin
  full_name: Sonntag, Konstantin
  id: '56399'
  last_name: Sonntag
  orcid: https://orcid.org/0000-0003-3384-3496
citation:
  ama: Bot RI, Sonntag K. Inertial dynamics with vanishing Tikhonov regularization
    for multobjective optimization. <i>Journal of Mathematical Analysis and Applications</i>.
    Published online 2025.
  apa: Bot, R. I., &#38; Sonntag, K. (2025). Inertial dynamics with vanishing Tikhonov
    regularization for multobjective optimization. <i>Journal of Mathematical Analysis
    and Applications</i>.
  bibtex: '@article{Bot_Sonntag_2025, title={Inertial dynamics with vanishing Tikhonov
    regularization for multobjective optimization}, journal={Journal of Mathematical
    Analysis and Applications}, author={Bot, Radu Ioan and Sonntag, Konstantin}, year={2025}
    }'
  chicago: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing
    Tikhonov Regularization for Multobjective Optimization.” <i>Journal of Mathematical
    Analysis and Applications</i>, 2025.
  ieee: R. I. Bot and K. Sonntag, “Inertial dynamics with vanishing Tikhonov regularization
    for multobjective optimization,” <i>Journal of Mathematical Analysis and Applications</i>,
    2025.
  mla: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing Tikhonov
    Regularization for Multobjective Optimization.” <i>Journal of Mathematical Analysis
    and Applications</i>, 2025.
  short: R.I. Bot, K. Sonntag, Journal of Mathematical Analysis and Applications (2025).
date_created: 2024-11-28T08:58:17Z
date_updated: 2025-10-16T11:56:36Z
ddc:
- '510'
department:
- _id: '101'
- _id: '530'
- _id: '655'
external_id:
  arxiv:
  - '2411.18422'
file:
- access_level: open_access
  content_type: application/pdf
  creator: sonntagk
  date_created: 2024-11-28T08:58:00Z
  date_updated: 2024-11-28T08:58:00Z
  file_id: '57473'
  file_name: Inertial dynamics with vanishing Tikhonov regularization for multobjective
    optimization.pdf
  file_size: 4291134
  relation: main_file
file_date_updated: 2024-11-28T08:58:00Z
has_accepted_license: '1'
keyword:
- Pareto optimization
- Lyapunov analysis
- gradient-like dynamical systems
- inertial dynamics
- asymptotic vanishing damping
- Tikhonov regularization
- strong convergence
language:
- iso: eng
main_file_link:
- url: https://arxiv.org/pdf/2411.18422
oa: '1'
publication: Journal of Mathematical Analysis and Applications
status: public
title: Inertial dynamics with vanishing Tikhonov regularization for multobjective
  optimization
type: journal_article
user_id: '56399'
year: '2025'
...
---
_id: '63053'
author:
- first_name: Carlos
  full_name: Hernández, Carlos
  last_name: Hernández
- first_name: Angel E.
  full_name: Rodriguez-Fernandez, Angel E.
  last_name: Rodriguez-Fernandez
- first_name: Lennart
  full_name: Schäpermeier, Lennart
  last_name: Schäpermeier
- first_name: Oliver
  full_name: Cuate, Oliver
  last_name: Cuate
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Oliver
  full_name: Schütze, Oliver
  last_name: Schütze
citation:
  ama: Hernández C, Rodriguez-Fernandez AE, Schäpermeier L, Cuate O, Trautmann H,
    Schütze O. An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
    for Multi-Objective Multimodal Optimization. <i>IEEE Transactions on Evolutionary
    Computation</i>. Published online 2025:1-1. doi:<a href="https://doi.org/10.1109/TEVC.2025.3637276">10.1109/TEVC.2025.3637276</a>
  apa: Hernández, C., Rodriguez-Fernandez, A. E., Schäpermeier, L., Cuate, O., Trautmann,
    H., &#38; Schütze, O. (2025). An Evolutionary Approach for the Computation of
    ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. <i>IEEE
    Transactions on Evolutionary Computation</i>, 1–1. <a href="https://doi.org/10.1109/TEVC.2025.3637276">https://doi.org/10.1109/TEVC.2025.3637276</a>
  bibtex: '@article{Hernández_Rodriguez-Fernandez_Schäpermeier_Cuate_Trautmann_Schütze_2025,
    title={An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
    for Multi-Objective Multimodal Optimization}, DOI={<a href="https://doi.org/10.1109/TEVC.2025.3637276">10.1109/TEVC.2025.3637276</a>},
    journal={IEEE Transactions on Evolutionary Computation}, author={Hernández, Carlos
    and Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Cuate, Oliver
    and Trautmann, Heike and Schütze, Oliver}, year={2025}, pages={1–1} }'
  chicago: Hernández, Carlos, Angel E. Rodriguez-Fernandez, Lennart Schäpermeier,
    Oliver Cuate, Heike Trautmann, and Oliver Schütze. “An Evolutionary Approach for
    the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal
    Optimization.” <i>IEEE Transactions on Evolutionary Computation</i>, 2025, 1–1.
    <a href="https://doi.org/10.1109/TEVC.2025.3637276">https://doi.org/10.1109/TEVC.2025.3637276</a>.
  ieee: 'C. Hernández, A. E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann,
    and O. Schütze, “An Evolutionary Approach for the Computation of ∈-Locally Optimal
    Solutions for Multi-Objective Multimodal Optimization,” <i>IEEE Transactions on
    Evolutionary Computation</i>, pp. 1–1, 2025, doi: <a href="https://doi.org/10.1109/TEVC.2025.3637276">10.1109/TEVC.2025.3637276</a>.'
  mla: Hernández, Carlos, et al. “An Evolutionary Approach for the Computation of
    ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” <i>IEEE
    Transactions on Evolutionary Computation</i>, 2025, pp. 1–1, doi:<a href="https://doi.org/10.1109/TEVC.2025.3637276">10.1109/TEVC.2025.3637276</a>.
  short: C. Hernández, A.E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann,
    O. Schütze, IEEE Transactions on Evolutionary Computation (2025) 1–1.
date_created: 2025-12-12T06:13:06Z
date_updated: 2025-12-12T06:13:51Z
department:
- _id: '819'
doi: 10.1109/TEVC.2025.3637276
keyword:
- Optimization
- Evolutionary computation
- Hands
- Proposals
- Convergence
- Computational efficiency
- Artificial intelligence
- Accuracy
- Approximation algorithms
- Aerospace electronics
- Multi-objective optimization
- evolutionary algorithms
- nearly optimal solutions
- multimodal optimization
- archiving
- continuation
language:
- iso: eng
page: 1-1
publication: IEEE Transactions on Evolutionary Computation
status: public
title: An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
  for Multi-Objective Multimodal Optimization
type: journal_article
user_id: '15504'
year: '2025'
...
---
_id: '32447'
abstract:
- lang: eng
  text: 'We present a new gradient-like dynamical system related to unconstrained
    convex smooth multiobjective optimization which involves inertial effects and
    asymptotic vanishing damping. To the best of our knowledge, this system is the
    first inertial gradient-like system for multiobjective optimization problems including
    asymptotic vanishing damping, expanding the ideas previously laid out in [H. Attouch
    and G. Garrigos, Multiobjective Optimization: An Inertial Dynamical Approach to
    Pareto Optima, preprint, arXiv:1506.02823, 2015]. We prove existence of solutions
    to this system in finite dimensions and further prove that its bounded solutions
    converge weakly to weakly Pareto optimal points. In addition, we obtain a convergence
    rate of order \(\mathcal{O}(t^{-2})\) for the function values measured with a
    merit function. This approach presents a good basis for the development of fast
    gradient methods for multiobjective optimization.'
article_type: original
author:
- first_name: Konstantin
  full_name: Sonntag, Konstantin
  id: '56399'
  last_name: Sonntag
  orcid: https://orcid.org/0000-0003-3384-3496
- first_name: Sebastian
  full_name: Peitz, Sebastian
  id: '47427'
  last_name: Peitz
  orcid: 0000-0002-3389-793X
citation:
  ama: Sonntag K, Peitz S. Fast Convergence of Inertial Multiobjective Gradient-Like
    Systems with Asymptotic Vanishing Damping. <i>SIAM Journal on Optimization</i>.
    2024;34(3):2259-2286. doi:<a href="https://doi.org/10.1137/23M1588512">10.1137/23M1588512</a>
  apa: Sonntag, K., &#38; Peitz, S. (2024). Fast Convergence of Inertial Multiobjective
    Gradient-Like Systems with Asymptotic Vanishing Damping. <i>SIAM Journal on Optimization</i>,
    <i>34</i>(3), 2259–2286. <a href="https://doi.org/10.1137/23M1588512">https://doi.org/10.1137/23M1588512</a>
  bibtex: '@article{Sonntag_Peitz_2024, title={Fast Convergence of Inertial Multiobjective
    Gradient-Like Systems with Asymptotic Vanishing Damping}, volume={34}, DOI={<a
    href="https://doi.org/10.1137/23M1588512">10.1137/23M1588512</a>}, number={3},
    journal={SIAM Journal on Optimization}, publisher={Society for Industrial and
    Applied Mathematics}, author={Sonntag, Konstantin and Peitz, Sebastian}, year={2024},
    pages={2259–2286} }'
  chicago: 'Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial
    Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping.” <i>SIAM
    Journal on Optimization</i> 34, no. 3 (2024): 2259–86. <a href="https://doi.org/10.1137/23M1588512">https://doi.org/10.1137/23M1588512</a>.'
  ieee: 'K. Sonntag and S. Peitz, “Fast Convergence of Inertial Multiobjective Gradient-Like
    Systems with Asymptotic Vanishing Damping,” <i>SIAM Journal on Optimization</i>,
    vol. 34, no. 3, pp. 2259–2286, 2024, doi: <a href="https://doi.org/10.1137/23M1588512">10.1137/23M1588512</a>.'
  mla: Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial Multiobjective
    Gradient-Like Systems with Asymptotic Vanishing Damping.” <i>SIAM Journal on Optimization</i>,
    vol. 34, no. 3, Society for Industrial and Applied Mathematics, 2024, pp. 2259–86,
    doi:<a href="https://doi.org/10.1137/23M1588512">10.1137/23M1588512</a>.
  short: K. Sonntag, S. Peitz, SIAM Journal on Optimization 34 (2024) 2259–2286.
date_created: 2022-07-28T11:53:02Z
date_updated: 2024-07-02T09:27:39Z
department:
- _id: '101'
- _id: '655'
doi: 10.1137/23M1588512
intvolume: '        34'
issue: '3'
keyword:
- multiobjective optimization
- Pareto optimization
- Lyapunov analysis
- gradient-likedynamical systems
- inertial dynamics
- asymptotic vanishing damping
- fast convergence
language:
- iso: eng
page: 2259 - 2286
publication: SIAM Journal on Optimization
publication_identifier:
  issn:
  - 1095-7189
publication_status: published
publisher: Society for Industrial and Applied Mathematics
status: public
title: Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic
  Vanishing Damping
type: journal_article
user_id: '56399'
volume: 34
year: '2024'
...
---
_id: '17653'
author:
- first_name: Gleb
  full_name: Polevoy, Gleb
  id: '83983'
  last_name: Polevoy
- first_name: M.M.
  full_name: de Weerdt, M.M.
  last_name: de Weerdt
citation:
  ama: 'Polevoy G, de Weerdt MM. Reciprocation Effort Games. In: <i>Proceedings of
    the 29th Benelux Conference on Artificial Intelligence</i>. CCIS. Springer; 2017.'
  apa: Polevoy, G., &#38; de Weerdt, M. M. (2017). Reciprocation Effort Games. In
    <i>Proceedings of the 29th Benelux Conference on Artificial Intelligence</i>.
    Springer.
  bibtex: '@inproceedings{Polevoy_de Weerdt_2017, series={CCIS}, title={Reciprocation
    Effort Games}, booktitle={Proceedings of the 29th Benelux Conference on Artificial
    Intelligence}, publisher={Springer}, author={Polevoy, Gleb and de Weerdt, M.M.},
    year={2017}, collection={CCIS} }'
  chicago: Polevoy, Gleb, and M.M. de Weerdt. “Reciprocation Effort Games.” In <i>Proceedings
    of the 29th Benelux Conference on Artificial Intelligence</i>. CCIS. Springer,
    2017.
  ieee: G. Polevoy and M. M. de Weerdt, “Reciprocation Effort Games,” in <i>Proceedings
    of the 29th Benelux Conference on Artificial Intelligence</i>, 2017.
  mla: Polevoy, Gleb, and M. M. de Weerdt. “Reciprocation Effort Games.” <i>Proceedings
    of the 29th Benelux Conference on Artificial Intelligence</i>, Springer, 2017.
  short: 'G. Polevoy, M.M. de Weerdt, in: Proceedings of the 29th Benelux Conference
    on Artificial Intelligence, Springer, 2017.'
date_created: 2020-08-06T15:20:09Z
date_updated: 2022-01-06T06:53:16Z
department:
- _id: '63'
- _id: '541'
extern: '1'
keyword:
- interaction
- reciprocation
- contribute
- shared effort
- curbing
- convergence
- threshold
- Nash equilibrium
- social welfare
- efficiency
- price of anarchy
- price of stability
language:
- iso: eng
publication: Proceedings of the 29th Benelux Conference on Artificial Intelligence
publisher: Springer
series_title: CCIS
status: public
title: Reciprocation Effort Games
type: conference
user_id: '83983'
year: '2017'
...
---
_id: '48857'
abstract:
- lang: eng
  text: 'While finding minimum-cost spanning trees (MST) in undirected graphs is solvable
    in polynomial time, the multi-criteria minimum spanning tree problem (mcMST) is
    NP-hard. Interestingly, the mcMST problem has not been in focus of evolutionary
    computation research for a long period of time, although, its relevance for real
    world problems is easy to see. The available and most notable approaches by Zhou
    and Gen as well as by Knowles and Corne concentrate on solution encoding and on
    fairly dated selection mechanisms. In this work, we revisit the mcMST and focus
    on the mutation operators as exploratory components of evolutionary algorithms
    neglected so far. We investigate optimal solution characteristics to discuss current
    mutation strategies, identify shortcomings of these operators, and propose a sub-tree
    based operator which offers what we term Pareto-beneficial behavior: ensuring
    convergence and diversity at the same time. The operator is empirically evaluated
    inside modern standard evolutionary meta-heuristics for multi-criteria optimization
    and compared to hitherto applied mutation operators in the context of mcMST.'
author:
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Christian
  full_name: Grimme, Christian
  last_name: Grimme
citation:
  ama: 'Bossek J, Grimme C. A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria
    Minimum Spanning Tree Problem. In: <i>2017 IEEE Symposium Series on Computational
    Intelligence (SSCI)</i>. ; 2017:1–8. doi:<a href="https://doi.org/10.1109/SSCI.2017.8285183">10.1109/SSCI.2017.8285183</a>'
  apa: Bossek, J., &#38; Grimme, C. (2017). A Pareto-Beneficial Sub-Tree Mutation
    for the Multi-Criteria Minimum Spanning Tree Problem. <i>2017 IEEE Symposium Series
    on Computational Intelligence (SSCI)</i>, 1–8. <a href="https://doi.org/10.1109/SSCI.2017.8285183">https://doi.org/10.1109/SSCI.2017.8285183</a>
  bibtex: '@inproceedings{Bossek_Grimme_2017, title={A Pareto-Beneficial Sub-Tree
    Mutation for the Multi-Criteria Minimum Spanning Tree Problem}, DOI={<a href="https://doi.org/10.1109/SSCI.2017.8285183">10.1109/SSCI.2017.8285183</a>},
    booktitle={2017 IEEE Symposium Series on Computational Intelligence (SSCI)}, author={Bossek,
    Jakob and Grimme, Christian}, year={2017}, pages={1–8} }'
  chicago: Bossek, Jakob, and Christian Grimme. “A Pareto-Beneficial Sub-Tree Mutation
    for the Multi-Criteria Minimum Spanning Tree Problem.” In <i>2017 IEEE Symposium
    Series on Computational Intelligence (SSCI)</i>, 1–8, 2017. <a href="https://doi.org/10.1109/SSCI.2017.8285183">https://doi.org/10.1109/SSCI.2017.8285183</a>.
  ieee: 'J. Bossek and C. Grimme, “A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria
    Minimum Spanning Tree Problem,” in <i>2017 IEEE Symposium Series on Computational
    Intelligence (SSCI)</i>, 2017, pp. 1–8, doi: <a href="https://doi.org/10.1109/SSCI.2017.8285183">10.1109/SSCI.2017.8285183</a>.'
  mla: Bossek, Jakob, and Christian Grimme. “A Pareto-Beneficial Sub-Tree Mutation
    for the Multi-Criteria Minimum Spanning Tree Problem.” <i>2017 IEEE Symposium
    Series on Computational Intelligence (SSCI)</i>, 2017, pp. 1–8, doi:<a href="https://doi.org/10.1109/SSCI.2017.8285183">10.1109/SSCI.2017.8285183</a>.
  short: 'J. Bossek, C. Grimme, in: 2017 IEEE Symposium Series on Computational Intelligence
    (SSCI), 2017, pp. 1–8.'
date_created: 2023-11-14T15:58:54Z
date_updated: 2023-12-13T10:44:28Z
department:
- _id: '819'
doi: 10.1109/SSCI.2017.8285183
extern: '1'
keyword:
- Convergence
- Encoding
- Euclidean distance
- Evolutionary computation
- Heating systems
- Optimization
- Standards
language:
- iso: eng
page: 1–8
publication: 2017 IEEE Symposium Series on Computational Intelligence (SSCI)
publication_status: published
status: public
title: A Pareto-Beneficial Sub-Tree Mutation for the Multi-Criteria Minimum Spanning
  Tree Problem
type: conference
user_id: '102979'
year: '2017'
...
---
_id: '17656'
author:
- first_name: Gleb
  full_name: Polevoy, Gleb
  id: '83983'
  last_name: Polevoy
- first_name: Mathijs
  full_name: de Weerdt, Mathijs
  last_name: de Weerdt
- first_name: Catholijn
  full_name: Jonker, Catholijn
  last_name: Jonker
citation:
  ama: 'Polevoy G, de Weerdt M, Jonker C. The Convergence of Reciprocation. In: <i>Proceedings
    of the 2016 International Conference on Autonomous Agents and Multiagent Systems</i>.
    AAMAS ’16. Richland, SC: International Foundation for Autonomous Agents and Multiagent
    Systems; 2016:1431-1432.'
  apa: 'Polevoy, G., de Weerdt, M., &#38; Jonker, C. (2016). The Convergence of Reciprocation.
    In <i>Proceedings of the 2016 International Conference on Autonomous Agents and
    Multiagent Systems</i> (pp. 1431–1432). Richland, SC: International Foundation
    for Autonomous Agents and Multiagent Systems.'
  bibtex: '@inproceedings{Polevoy_de Weerdt_Jonker_2016, place={Richland, SC}, series={AAMAS
    ’16}, title={The Convergence of Reciprocation}, booktitle={Proceedings of the
    2016 International Conference on Autonomous Agents and Multiagent Systems}, publisher={International
    Foundation for Autonomous Agents and Multiagent Systems}, author={Polevoy, Gleb
    and de Weerdt, Mathijs and Jonker, Catholijn}, year={2016}, pages={1431–1432},
    collection={AAMAS ’16} }'
  chicago: 'Polevoy, Gleb, Mathijs de Weerdt, and Catholijn Jonker. “The Convergence
    of Reciprocation.” In <i>Proceedings of the 2016 International Conference on Autonomous
    Agents and Multiagent Systems</i>, 1431–32. AAMAS ’16. Richland, SC: International
    Foundation for Autonomous Agents and Multiagent Systems, 2016.'
  ieee: G. Polevoy, M. de Weerdt, and C. Jonker, “The Convergence of Reciprocation,”
    in <i>Proceedings of the 2016 International Conference on Autonomous Agents and
    Multiagent Systems</i>, 2016, pp. 1431–1432.
  mla: Polevoy, Gleb, et al. “The Convergence of Reciprocation.” <i>Proceedings of
    the 2016 International Conference on Autonomous Agents and Multiagent Systems</i>,
    International Foundation for Autonomous Agents and Multiagent Systems, 2016, pp.
    1431–32.
  short: 'G. Polevoy, M. de Weerdt, C. Jonker, in: Proceedings of the 2016 International
    Conference on Autonomous Agents and Multiagent Systems, International Foundation
    for Autonomous Agents and Multiagent Systems, Richland, SC, 2016, pp. 1431–1432.'
date_created: 2020-08-06T15:20:45Z
date_updated: 2022-01-06T06:53:16Z
department:
- _id: '63'
- _id: '541'
extern: '1'
keyword:
- agent's influence
- behavior
- convergence
- perron-frobenius
- reciprocal interaction
- repeated reciprocation
language:
- iso: eng
page: 1431-1432
place: Richland, SC
publication: Proceedings of the 2016 International Conference on Autonomous Agents
  and Multiagent Systems
publication_identifier:
  isbn:
  - 978-1-4503-4239-1
publisher: International Foundation for Autonomous Agents and Multiagent Systems
series_title: AAMAS '16
status: public
title: The Convergence of Reciprocation
type: conference
user_id: '83983'
year: '2016'
...
---
_id: '11816'
abstract:
- lang: eng
  text: In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters
    of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the
    resulting Expectation Maximization (EM) algorithm delivers virtually biasfree
    and efficient estimates, and we discuss its convergence properties. We also discuss
    optimal classification in the presence of censored data. Censored data are frequently
    encountered in wireless LAN positioning systems based on the fingerprinting method
    employing signal strength measurements, due to the limited sensitivity of the
    portable devices. Experiments both on simulated and real-world data demonstrate
    the effectiveness of the proposed algorithms.
author:
- first_name: Manh Kha
  full_name: Hoang, Manh Kha
  last_name: Hoang
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored
    Gaussian data with application to WiFi indoor positioning. In: <i>38th International
    Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>. ; 2013:3721-3725.
    doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638353">10.1109/ICASSP.2013.6638353</a>'
  apa: Hoang, M. K., &#38; Haeb-Umbach, R. (2013). Parameter estimation and classification
    of censored Gaussian data with application to WiFi indoor positioning. In <i>38th
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>
    (pp. 3721–3725). <a href="https://doi.org/10.1109/ICASSP.2013.6638353">https://doi.org/10.1109/ICASSP.2013.6638353</a>
  bibtex: '@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and
    classification of censored Gaussian data with application to WiFi indoor positioning},
    DOI={<a href="https://doi.org/10.1109/ICASSP.2013.6638353">10.1109/ICASSP.2013.6638353</a>},
    booktitle={38th International Conference on Acoustics, Speech, and Signal Processing
    (ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013},
    pages={3721–3725} }'
  chicago: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
    of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In <i>38th
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>,
    3721–25, 2013. <a href="https://doi.org/10.1109/ICASSP.2013.6638353">https://doi.org/10.1109/ICASSP.2013.6638353</a>.
  ieee: M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of
    censored Gaussian data with application to WiFi indoor positioning,” in <i>38th
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>,
    2013, pp. 3721–3725.
  mla: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
    of Censored Gaussian Data with Application to WiFi Indoor Positioning.” <i>38th
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>,
    2013, pp. 3721–25, doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638353">10.1109/ICASSP.2013.6638353</a>.
  short: 'M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
    Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.'
date_created: 2019-07-12T05:28:48Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638353
keyword:
- Gaussian processes
- Global Positioning System
- convergence
- expectation-maximisation algorithm
- fingerprint identification
- indoor radio
- signal classification
- wireless LAN
- EM algorithm
- ML estimation
- WiFi indoor positioning
- censored Gaussian data classification
- clipped data
- convergence properties
- expectation maximization algorithm
- fingerprinting method
- maximum likelihood estimation
- optimal classification
- parameters estimation
- portable devices sensitivity
- signal strength measurements
- wireless LAN positioning systems
- Convergence
- IEEE 802.11 Standards
- Maximum likelihood estimation
- Parameter estimation
- Position measurement
- Training
- Indoor positioning
- censored data
- expectation maximization
- signal strength
- wireless LAN
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf
oa: '1'
page: 3721-3725
publication: 38th International Conference on Acoustics, Speech, and Signal Processing
  (ICASSP 2013)
publication_identifier:
  issn:
  - 1520-6149
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf
status: public
title: Parameter estimation and classification of censored Gaussian data with application
  to WiFi indoor positioning
type: conference
user_id: '44006'
year: '2013'
...