PhD Notes

Contents:

Papers

Contents:

To-read list

In argumentation:

  • Coalitions of arguments: A tool for handling bipolar argumentation frameworks

  • On the Gradual Acceptability of Arguments in Bipolar Weighted Argumentation Frameworks with Degrees of Trust

  • A Comparative Study of Ranking-based Semantics for Abstract Argumentation

  • Equational approach to argumentation networks

  • Argument Mining on Twitter: Arguments, Facts and Sources

  • Judgement aggregation in multi-agent argumentation

  • Credulous Acceptability, Poison Games and Modal Logic

  • Changing One’s Mind: Erase or Rewind? Possibilistic Belief Revision with Fuzzy Argumentation based on Trust

  • Capturing bipolar argumentation in non-flat assumption-based argumentation

  • Constructing and Evaluating Bipolar Weighted Argumentation Frameworks for Online Debating Systems

  • Gradual Semantics Accounting for Varied-Strength Attacks

  • Argumentation Semantics as Formal Discussion (Martin Caminada)

  • Fuzzy argumentation for trust

In TD:

  • Truth Discovery from Conflicting Multi-Valued Objects

  • Integrated and flexible framework for claim evaluation using credibility of sources

  • Constrained Truth Discovery

  • Automated evaluation of annotators for museum collections using subjective logic

  • Truth Discovery under Resource Constraints (PhD Thesis)

  • Truth Discovery by Claim and Source Embedding

  • On bayesian interpretation of fact-finding in information networks

  • Zencrowd: leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking.

  • People on drugs: Credibility of user statements in health communities

  • Content-driven trust propagation framework

  • Ensemble Classification Method Based on Truth Discovery

  • Learning the truth vector in high dimensions

  • Truth Discovery on Crowd Sensing of Correlated Entities

  • Whose vote should count more: optimal integration of labelers of unknown expertise

  • Automatic deception detection: Methods for finding fake news

  • Inferring Ground Truth From Crowdsourced Data Under Local Attribute Differential Privacy

  • A survey of trust in social networks, Sherchan

  • Truth Discovery via Proxy Voting

  • Knowledge-based trust: Estimating the trustworthiness of web sources

  • Neural network TD:

    • Truth discovery with memory network

    • Restricted Boltzmann Machines for Robust and Fast Latent Truth Discovery

    • Neural Network Architecture for Credibility Assessment of Textual Claims

    • A Neural Network Approach for Truth Discovery in Social Sensing

In social choice:

  • How Effective Can Simple Ordinal Peer Grading Be?

  • Generalized Decision Scoring Rules: Statistical, Computational, and Axiomatic Properties

  • Collective annotation of linguistic resources

  • Better human computation through principled voting

  • Graph aggregation, Endriss and Grandi

In belief revision:

  • The basic principles of uncertain information fusion. An organised review of merging rules in different representation frameworks

  • Logic-based approaches to information fusion

  • Logic Based Merging

  • Social choice theory, belief merging, and strategy-proofness

  • Belief merging versus Judgment Aggregation

Others:

  • Belief, information acquisition, and trust in multi agent systems – A modal logic formulation

  • The logic of justification

  • Truthful mobile crowd sensing with interdependent valuations

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ABN13

Leila Amgoud and Jonathan Ben-Naim. Ranking-based semantics for argumentation frameworks. In Weiru Liu, V. S. Subrahmanian, and Jef Wijsen, editors, Scalable Uncertainty Management, 134–147. Berlin, Heidelberg, 2013. Springer Berlin Heidelberg.

AD14

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AndjelicAC+15

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BGS19

Alexandru Baltag, Nina Gierasimczuk, and Sonja Smets. Truth-Tracking by Belief Revision. Studia Logica, 107(5):917–947, October 2019. URL: https://doi.org/10.1007/s11225-018-9812-x, doi:10.1007/s11225-018-9812-x.

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BRT19

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BBH16

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BCE+16

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BVazquezCCDiazRGonzalezDiaz08

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CS17

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CKV16

Ioannis Caragiannis, George A. Krimpas, and Alexandros A. Voudouris. How effective can simple ordinal peer grading be? In Proceedings of the 2016 ACM Conference on Economics and Computation, EC ’16, 323–340. New York, NY, USA, 2016. Association for Computing Machinery. URL: https://doi.org/10.1145/2940716.2940748, doi:10.1145/2940716.2940748.

CPS16

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CLS05a

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CLS05b

C. Cayrol and M. C. Lagasquie-Schiex. On the Acceptability of Arguments in Bipolar Argumentation Frameworks. In Lluís Godo, editor, Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 378–389. Berlin, Heidelberg, 2005. Springer Berlin Heidelberg.

CLagasquieSchiex13

Claudette Cayrol and Marie-Christine Lagasquie-Schiex. Bipolarity in argumentation graphs: towards a better understanding. Int. J. Approx. Reasoning, 54(7):876–899, 2013. URL: https://doi.org/10.1016/j.ijar.2013.03.001, doi:10.1016/j.ijar.2013.03.001.

Cev14

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CS99

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CRC15

Niall J. Conroy, Victoria L. Rubin, and Yimin Chen. Automatic deception detection: methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1):1–4, 2015. URL: https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/pra2.2015.145052010082, arXiv:https://asistdl.onlinelibrary.wiley.com/doi/pdf/10.1002/pra2.2015.145052010082, doi:10.1002/pra2.2015.145052010082.

CI15

David Cook II. Nested colorings of graphs. AUSTRALASIAN JOURNAL OF COMBINATORICS, 62(1):100–127, 2015.

Cro05

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Csato19

László Csató. An impossibility theorem for paired comparisons. Central European Journal of Operations Research, 27(2):497–514, 2019.

DDKR13

Nilesh Dalvi, Anirban Dasgupta, Ravi Kumar, and Vibhor Rastogi. Aggregating crowdsourced binary ratings. In Proceedings of the 22nd International Conference on World Wide Web, WWW ‘13, 285–294. New York, NY, USA, 2013. Association for Computing Machinery. URL: https://doi.org/10.1145/2488388.2488414, doi:10.1145/2488388.2488414.

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DPW18

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DGX16

Hu Ding, Jing Gao, and Jinhui Xu. Finding global optimum for truth discovery: entropy based geometric variance. In Proc. 32nd International Symposium on Computational Geometry (SoCG 2016). 2016.

DDLS15

Pål Grønås Drange, Markus Sortland Dregi, Daniel Lokshtanov, and Blair D Sullivan. On the threshold of intractability. In Algorithms-ESA 2015, pages 411–423. Springer, 2015.

EKM+10

Patricia Everaere, Sébastien Konieczny, Pierre Marquis, and others. The epistemic view of belief merging: can we track the truth?. In ECAI, 621–626. 2010.

FMHV03

Ronald Fagin, Yoram Moses, Joseph Y Halpern, and Moshe Y Vardi. Reasoning about knowledge. MIT press, 2003.

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GK17

Konstantin Genin and Kevin T Kelly. The topology of statistical verifiability. arXiv preprint arXiv:1707.09378, 2017.

GKM11

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GonzalezDiazHL14

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HKP+20

Daniel Halpern, Gregory Kehne, Dominik Peters, Ariel D Procaccia, Nisarg Shah, and Piotr Skowron. Aggregating binary judgments ranked by accuracy. ?, 2020.

HKMO18

Adrian Haret, Hossein Khani, Stefano Moretti, and Meltem Ozturk. Ceteris paribus majority for social ranking. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18. 2018.

HS12

Stephan Hartmann and Jan Sprenger. Judgment aggregation and the problem of tracking the truth. Synthese, 187(1):209–221, July 2012. URL: https://doi.org/10.1007/s11229-011-0031-5, doi:10.1007/s11229-011-0031-5.

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JDCV08

Jeroen Janssen, Martine De Cock, and Dirk Vermeir. Fuzzy argumentation frameworks. In Information processing and management of uncertainty in knowledge-based systems, 513–520. 2008.

JRG17

Yang Jiao, R Ravi, and Wolfgang Gatterbauer. Algorithms for automatic ranking of participants and tasks in an anonymized contest. In International Workshop on Algorithms and Computation, 335–346. Springer, 2017.

KOS13

David R. Karger, Sewoong Oh, and Devavrat Shah. Efficient crowdsourcing for multi-class labeling. In Proceedings of the ACM SIGMETRICS/International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS ‘13, 81–92. New York, NY, USA, 2013. Association for Computing Machinery. URL: https://doi.org/10.1145/2465529.2465761, doi:10.1145/2465529.2465761.

KSH97

Kevin Kelly, Oliver Schulte, and Vincent Hendricks. Reliable belief revision. In Logic and Scientific Methods, pages 383–398. Springer, 1997.

Kle99

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KPerez08

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KEFQ14

Justin Kruger, Ulle Endriss, Raquel Fernandez, and Ciyang Qing. Axiomatic Analysis of Aggregation Methods for Collective Annotation. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems, AAMAS ‘14, 1185–1192. Richland, SC, 2014. International Foundation for Autonomous Agents and Multiagent Systems. event-place: Paris, France. URL: http://dl.acm.org/citation.cfm?id=2617388.2617437.

LLG+14

Qi Li, Yaliang Li, Jing Gao, Lu Su, Bo Zhao, Murat Demirbas, Wei Fan, and Jiawei Han. A confidence-aware approach for truth discovery on long-tail data. Proc. VLDB Endow., 8(4):425–436, December 2014. URL: https://doi.org/10.14778/2735496.2735505, doi:10.14778/2735496.2735505.

LLG+16

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, and Jiawei Han. Conflicts to Harmony: A Framework for Resolving Conflicts in Heterogeneous Data by Truth Discovery. IEEE Transactions on Knowledge and Data Engineering, 28(8):1986–1999, August 2016. doi:10.1109/TKDE.2016.2559481.

MSH20

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OBB+18

Catherine Olsson, Surya Bhupatiraju, Tom Brown, Augustus Odena, and Ian Goodfellow. Skill rating for generative models. arXiv preprint arXiv:1808.04888, 2018.

Pac17

Eric Pacuit. Neighborhood semantics for modal logic. Springer, 2017.

PTS+11

Simon Parsons, Yuqing Tang, Elizabeth Sklar, Peter McBurney, and Kai Cai. Argumentation-based reasoning in agents with varying degrees of trust. In The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2, AAMAS ‘11, 879–886. Richland, SC, 2011. International Foundation for Autonomous Agents and Multiagent Systems. URL: http://dl.acm.org/citation.cfm?id=2031678.2031743.

PR10

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XGW+16

Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, and Han Liu. A Truth Discovery Approach with Theoretical Guarantee. In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ‘16, 1925–1934. New York, NY, USA, 2016. ACM. event-place: San Francisco, California, USA. URL: http://doi.acm.org/10.1145/2939672.2939816, doi:10.1145/2939672.2939816.

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