Gjergji Kasneci

Orcid: 0000-0002-3123-7268

Affiliations:
  • Technical University of Munich, Germany
  • University of Tübingen, Germany (former)
  • Hasso Plattner Institute, Potsdam, Germany (former)
  • Microsoft Research (former)
  • Max-Planck Institute for Informatics, Saarbrücken, Germany (former)


According to our database1, Gjergji Kasneci authored at least 107 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
Towards Human-Centered Explainable AI: A Survey of User Studies for Model Explanations.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024

Towards Non-Adversarial Algorithmic Recourse.
CoRR, 2024

Is Crowdsourcing Breaking Your Bank? Cost-Effective Fine-Tuning of Pre-trained Language Models with Proximal Policy Optimization.
CoRR, 2024

User Intent Recognition and Satisfaction with Large Language Models: A User Study with ChatGPT.
CoRR, 2024

Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education.
CoRR, 2024

I Prefer Not to Say: Protecting User Consent in Models with Optional Personal Data.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
DeepTLF: robust deep neural networks for heterogeneous tabular data.
Int. J. Data Sci. Anal., June, 2023

Adversarial Reweighting Guided by Wasserstein Distance for Bias Mitigation.
CoRR, 2023

Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes.
CoRR, 2023

Counterfactual Explanation via Search in Gaussian Mixture Distributed Latent Space.
CoRR, 2023

Explanation Shift: Investigating Interactions between Models and Shifting Data Distributions.
CoRR, 2023

When are post-hoc conceptual explanations identifiable?
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Gaussian Membership Inference Privacy.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Trade-Off between Actionable Explanations and the Right to be Forgotten.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Language Models are Realistic Tabular Data Generators.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Could Human Gaze Augment Detectors of Synthetic Images?
Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Counterfactual Explanation for Regression via Disentanglement in Latent Space.
Proceedings of the IEEE International Conference on Data Mining, 2023

Causal Fairness-Guided Dataset Reweighting using Neural Networks.
Proceedings of the IEEE International Conference on Big Data, 2023

Can You Solve This on the First Try? - Understanding Exercise Field Performance in an Intelligent Tutoring System.
Proceedings of the Artificial Intelligence in Education - 24th International Conference, 2023

Interventional SHAP Values and Interaction Values for Piecewise Linear Regression Trees.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Relational Local Explanations.
CoRR, 2022

Expert Selection in Distributed Gaussian Processes: A Multi-label Classification Approach.
CoRR, 2022

Decomposing Counterfactual Explanations for Consequential Decision Making.
CoRR, 2022

I Prefer not to Say: Operationalizing Fair and User-guided Data Minimization.
CoRR, 2022

Explanation Shift: Detecting distribution shifts on tabular data via the explanation space.
CoRR, 2022

Towards Human-centered Explainable AI: User Studies for Model Explanations.
CoRR, 2022

Disentangling Embedding Spaces with Minimal Distributional Assumptions.
CoRR, 2022

Standardized Evaluation of Machine Learning Methods for Evolving Data Streams.
CoRR, 2022

Algorithmic Recourse in the Face of Noisy Human Responses.
CoRR, 2022

Gaussian Graphical Models as an Ensemble Method for Distributed Gaussian Processes.
CoRR, 2022

Evaluating Feature Attribution: An Information-Theoretic Perspective.
CoRR, 2022

BoxShrink: From Bounding Boxes to Segmentation Masks.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2022

A Consistent and Efficient Evaluation Strategy for Attribution Methods.
Proceedings of the International Conference on Machine Learning, 2022

Dynamic Model Tree for Interpretable Data Stream Learning.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Regressive Saccadic Eye Movements on Fake News.
Proceedings of the ETRA 2022: Symposium on Eye Tracking Research and Applications, Seattle, WA, USA, June 8, 2022

Change Detection for Local Explainability in Evolving Data Streams.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Aggregating the Gaussian Experts' Predictions via Undirected Graphical Models.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2022

Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines.
CoRR, 2021

Deep Neural Networks and Tabular Data: A Survey.
CoRR, 2021

Gaussian Experts Selection using Graphical Models.
CoRR, 2021

On Baselines for Local Feature Attributions.
CoRR, 2021

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

TEyeD: Over 20 Million Real-World Eye Images with Pupil, Eyelid, and Iris 2D and 3D Segmentations, 2D and 3D Landmarks, 3D Eyeball, Gaze Vector, and Eye Movement Types.
Proceedings of the IEEE International Symposium on Mixed and Augmented Reality, 2021

SPARROW: Semantically Coherent Prototypes for Image Classification.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Model Selection in Local Approximation Gaussian Processes: A Markov Random Fields Approach.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Bias in data-driven artificial intelligence systems - An introductory survey.
WIREs Data Mining Knowl. Discov., 2020

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots.
CoRR, 2020

Bias in Data-driven AI Systems - An Introductory Survey.
CoRR, 2020

Learning Model-Agnostic Counterfactual Explanations for Tabular Data.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

On Counterfactual Explanations under Predictive Multiplicity.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Leveraging Model Inherent Variable Importance for Stable Online Feature Selection.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Aggregating Dependent Gaussian Experts in Local Approximation.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Learning Parameter Distributions to Detect Concept Drift in Data Streams.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

A MinHash approach for fast scanpath classification.
Proceedings of the ETRA '20: 2020 Symposium on Eye Tracking Research and Applications, 2020

Training Decision Trees as Replacement for Convolution Layers.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Towards User Empowerment.
CoRR, 2019

Validation loss for landmark detection.
CoRR, 2019

A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

CancelOut: A Layer for Feature Selection in Deep Neural Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

2018
Combining Restricted Boltzmann Machines with Neural Networks for Latent Truth Discovery.
CoRR, 2018

Restricted Boltzmann Machines for Robust and Fast Latent Truth Discovery.
CoRR, 2018

2017
PupilNet v2.0: Convolutional Neural Networks for CPU based real time Robust Pupil Detection.
CoRR, 2017

Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth.
Comput. Hum. Behav., 2017

LTD-RBM: Robust and Fast Latent Truth Discovery Using Restricted Boltzmann Machines.
Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

2016
CohEEL: Coherent and efficient named entity linking through random walks.
J. Web Semant., 2016

PupilNet: Convolutional Neural Networks for Robust Pupil Detection.
CoRR, 2016

LICON: A Linear Weighting Scheme for the Contribution ofInput Variables in Deep Artificial Neural Networks.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Tweet-Recommender: Finding Relevant Tweets for News Articles.
Proceedings of the 24th International Conference on World Wide Web Companion, 2015

A Serendipity Model for News Recommendation.
Proceedings of the KI 2015: Advances in Artificial Intelligence, 2015

2014
Assigning global relevance scores to DBpedia facts.
Proceedings of the Workshops Proceedings of the 30th International Conference on Data Engineering Workshops, 2014

Bootstrapping Wikipedia to answer ambiguous person name queries.
Proceedings of the Workshops Proceedings of the 30th International Conference on Data Engineering Workshops, 2014

The applicability of probabilistic methods to the online recognition of fixations and saccades in dynamic scenes.
Proceedings of the Eye Tracking Research and Applications, 2014

BEL: Bagging for Entity Linking.
Proceedings of the COLING 2014, 2014

Estimating the Number and Sizes of Fuzzy-Duplicate Clusters.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Temporal Anomaly Detection in Business Processes.
Proceedings of the Business Process Management - 12th International Conference, 2014

Rule-based Classification of Visual Field Defects.
Proceedings of the HEALTHINF 2014, 2014

2013
Bootstrapped Grouping of Results to Ambiguous Person Name Queries.
CoRR, 2013

Analyzing and predicting viral tweets.
Proceedings of the 22nd International World Wide Web Conference, 2013

SIGMa: simple greedy matching for aligning large knowledge bases.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Online Classification of Eye Tracking Data for Automated Analysis of Traffic Hazard Perception.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012
Graffiti: graph-based classification in heterogeneous networks.
World Wide Web, 2012

Crowd IQ: measuring the intelligence of crowdsourcing platforms.
Proceedings of the Web Science 2012, 2012

Reasoning about Knowledge from the Web - (Extended Abstract).
Proceedings of the Current Trends in Web Engineering, 2012

Bayesian online clustering of eye movement data.
Proceedings of the 2012 Symposium on Eye-Tracking Research and Applications, 2012

Latent topics in graph-structured data.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Crowd IQ: aggregating opinions to boost performance.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
CoBayes: bayesian knowledge corroboration with assessors of unknown areas of expertise.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Automated feature generation from structured knowledge.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

DBrev: Dreaming of a Database Revolution.
Proceedings of the Fifth Biennial Conference on Innovative Data Systems Research, 2011

2010
Active knowledge: dynamically enriching RDF knowledge bases by web services.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2010

Bayesian Knowledge Corroboration with Logical Rules and User Feedback.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Searching and ranking in entity-relationship graphs.
PhD thesis, 2009

ANGIE: Active Knowledge for Interactive Exploration.
Proc. VLDB Endow., 2009

Database and information-retrieval methods for knowledge discovery.
Commun. ACM, 2009

Graffiti: node labeling in heterogeneous networks.
Proceedings of the 18th International Conference on World Wide Web, 2009

STAR: Steiner-Tree Approximation in Relationship Graphs.
Proceedings of the 25th International Conference on Data Engineering, 2009

MING: mining informative entity relationship subgraphs.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008
YAGO: A Large Ontology from Wikipedia and WordNet.
J. Web Semant., 2008

The YAGO-NAGA approach to knowledge discovery.
SIGMOD Rec., 2008

NAGA: harvesting, searching and ranking knowledge.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2008

NAGA: Searching and Ranking Knowledge.
Proceedings of the 24th International Conference on Data Engineering, 2008

2007
Yago: a core of semantic knowledge.
Proceedings of the 16th International Conference on World Wide Web, 2007

How NAGA uncoils: searching with entities and relations.
Proceedings of the 16th International Conference on World Wide Web, 2007

The complexity of reasoning about pattern-based XML schemas.
Proceedings of the Twenty-Sixth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2007

YAWN: A Semantically Annotated Wikipedia XML Corpus.
Proceedings of the Datenbanksysteme in Business, 2007


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