Fredrik D. Johansson

According to our database, Fredrik D. Johansson authored at least 52 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How Should We Represent History in Interpretable Models of Clinical Policies?

Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin, Heather J. Litman, Fredrik D. Johansson

CoRR, 2024

Expert Study on Interpretable Machine Learning Models with Missing Data.

Lena Stempfle, Arthur James, Julie Josse, Tobias Gauss, Fredrik D. Johansson

CoRR, 2024

Overcoming label shift in targeted federated learning.

Edvin Listo Zec, Adam Breitholtz, Fredrik D. Johansson

CoRR, 2024

Identifiable latent bandits: Combining observational data and exploration for personalized healthcare.

Ahmet Zahid Balcioglu, Emil Carlsson, Fredrik D. Johansson

CoRR, 2024

IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark.

Fredrik D. Johansson

CoRR, 2024

Active Preference Learning for Ordering Items In- and Out-of-sample.

Herman Bergström, Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

CoRR, 2024

MINTY: Rule-based models that minimize the need for imputing features with missing values.

Lena Stempfle, Fredrik D. Johansson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Pure Exploration in Bandits with Linear Constraints.

Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Fast Treatment Personalization with Latent Bandits in Fixed-Confidence Pure Exploration.

Newton Mwai Kinyanjui, Emil Carlsson, Fredrik D. Johansson

Trans. Mach. Learn. Res., 2023

Off-Policy Evaluation with Out-of-Sample Guarantees.

Sofia Ek, Dave Zachariah, Fredrik D. Johansson, Peter Stoica

Trans. Mach. Learn. Res., 2023

Unsupervised domain adaptation by learning using privileged information.

Adam Breitholtz, Anton Matsson, Fredrik D. Johansson

CoRR, 2023

Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities.

Connor T. Jerzak, Fredrik D. Johansson, Adel Daoud

CoRR, 2023

Time Series of Satellite Imagery Improve Deep Learning Estimates of Neighborhood-Level Poverty in Africa.

Markus B. Pettersson, Mohammad Kakooei, Julia Ortheden, Fredrik D. Johansson, Adel Daoud

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Image-based Treatment Effect Heterogeneity.

Connor Thomas Jerzak, Fredrik Daniel Johansson, Adel Daoud

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Sharing Pattern Submodels for Prediction with Missing Values.

Lena Stempfle, Ashkan Panahi, Fredrik D. Johansson

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Practicality of generalization guarantees for unsupervised domain adaptation with neural networks.

Adam Breitholtz, Fredrik D. Johansson

Trans. Mach. Learn. Res., 2022

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects.

Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David A. Sontag

J. Mach. Learn. Res., 2022

Sharing pattern submodels for prediction with missing values.

Lena Stempfle, Fredrik D. Johansson

CoRR, 2022

Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa.

Connor T. Jerzak, Fredrik Johansson, Adel Daoud

CoRR, 2022

Using satellites and artificial intelligence to measure health and material-living standards in India.

Adel Daoud, Felipe Jordan, Makkunda Sharma, Fredrik D. Johansson, Devdatt P. Dubhashi, Sourabh Bikash Paul, Subhashis Banerjee

CoRR, 2022

Case-based off-policy evaluation using prototype learning.

Anton Matsson, Fredrik D. Johansson

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Efficient learning of nonlinear prediction models with time-series privileged information.

Bastian Jung, Fredrik D. Johansson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ADCB: An Alzheimer's disease simulator for benchmarking observational estimators of causal effects.

Newton Mwai Kinyanjui, Fredrik D. Johansson

Proceedings of the Conference on Health, Inference, and Learning, 2022

Using time-series privileged information for provably efficient learning of prediction models.

Rickard K. A. Karlsson, Martin Willbo, Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag, Fredrik Johansson

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Case-based off-policy policy evaluation using prototype learning.

Anton Matsson, Fredrik D. Johansson

CoRR, 2021

ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects.

Newton Mwai Kinyanjui, Fredrik D. Johansson

CoRR, 2021

Thompson Sampling for Bandits with Clustered Arms.

Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Approximate and Exact Numeral Systems via Reinforcement Learning.

Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

A survey on graph kernels.

Nils M. Kriege, Fredrik D. Johansson, Christopher Morris

Appl. Netw. Sci., 2020

Learning to search efficiently for causally near-optimal treatments.

Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Estimation of Bounds on Potential Outcomes For Decision Making.

Maggie Makar, Fredrik D. Johansson, John V. Guttag, David A. Sontag

Proceedings of the 37th International Conference on Machine Learning, 2020

Characterization of Overlap in Observational Studies.

Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Estimation of Utility-Maximizing Bounds on Potential Outcomes.

Maggie Makar, Fredrik D. Johansson, John V. Guttag, David A. Sontag

CoRR, 2019

Support and Invertibility in Domain-Invariant Representations.

Fredrik D. Johansson, David A. Sontag, Rajesh Ranganath

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions.

Fredrik D. Johansson

CoRR, 2018

Evaluating Reinforcement Learning Algorithms in Observational Health Settings.

Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez

CoRR, 2018

Why Is My Classifier Discriminatory?

Irene Y. Chen, Fredrik D. Johansson, David A. Sontag

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Estimating individual treatment effect: generalization bounds and algorithms.

Uri Shalit, Fredrik D. Johansson, David A. Sontag

Proceedings of the 34th International Conference on Machine Learning, 2017

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery.

Ashkan Panahi, Devdatt P. Dubhashi, Fredrik D. Johansson, Chiranjib Bhattacharyya

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Learning with Geometric Embeddings of Graphs.

Fredrik Johansson

PhD thesis, 2016

Bounding and Minimizing Counterfactual Error.

Uri Shalit, Fredrik D. Johansson, David A. Sontag

CoRR, 2016

Learning Representations for Counterfactual Inference.

Fredrik D. Johansson, Uri Shalit, David A. Sontag

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Visions and open challenges for a knowledge-based culturomics.

Nina Tahmasebi, Lars Borin, Gabriele Capannini, Devdatt P. Dubhashi, Peter Exner, Markus Forsberg, Gerhard Gossen, Fredrik D. Johansson, Richard Johansson, Mikael Kågebäck, Olof Mogren, Pierre Nugues, Thomas Risse

Int. J. Digit. Libr., 2015

Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization.

Fredrik D. Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Neural context embeddings for automatic discovery of word senses.

Mikael Kågebäck, Fredrik D. Johansson, Richard Johansson, Devdatt P. Dubhashi

Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, 2015

Classifying Large Graphs with Differential Privacy.

Fredrik D. Johansson, Otto Frost, Carl Retzner, Devdatt P. Dubhashi

Proceedings of the Modeling Decisions for Artificial Intelligence, 2015

Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings.

Fredrik D. Johansson, Devdatt P. Dubhashi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Generalized Shortest Path Kernel on Graphs.

Linus Hermansson, Fredrik D. Johansson, Osamu Watanabe

Proceedings of the Discovery Science - 18th International Conference, 2015

2014

Global graph kernels using geometric embeddings.

Fredrik D. Johansson, Vinay Jethava, Devdatt P. Dubhashi, Chiranjib Bhattacharyya

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

DLOREAN: Dynamic Location-Aware Reconstruction of Multiway Networks.

Fredrik Johansson, Vinay Jethava, Devdatt P. Dubhashi

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Entity disambiguation in anonymized graphs using graph kernels.

Linus Hermansson, Tommi Kerola, Fredrik Johansson, Vinay Jethava, Devdatt P. Dubhashi

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012

Intent-aware temporal query modeling for keyword suggestion.

Fredrik Johansson, Tobias Färdig, Vinay Jethava, Svetoslav Marinov

Proceedings of the 5th Ph.D. Workshop on Information and Knowledge Management, 2012