Fredrik D. Johansson

71 papers A* 15A 5B 3Journal 44Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Expanding the Action Space of LLMs to Reason Beyond Language. CoRR Zhongqi Yue, Weishi Wang, Yundaichuan Zhan, Juncheng Li, Daniel Dahlmeier, Fredrik D. Johansson
2025	J	`jnl`	Federated Learning with Heterogeneous and Private Label Sets. CoRR Adam Breitholtz, Edvin Listo Zec, Fredrik D. Johansson
2025	J	`jnl`	Latent Preference Bandits. CoRR Newton Mwai Kinyanjui, Emil Carlsson, Fredrik D. Johansson
2025	J	`jnl`	Pragmatic Policy Development via Interpretable Behavior Cloning. CoRR Anton Matsson, Yaochen Rao, Heather J. Litman, Fredrik D. Johansson
2025	J	`jnl`	Prediction Models That Learn to Avoid Missing Values. CoRR Lena Stempfle, Anton Matsson, Newton Mwai Kinyanjui, Fredrik D. Johansson
2025	A*	`conf`	Prediction models that learn to avoid missing values. ICML Lena Stempfle, Anton Matsson, Newton Mwai Kinyanjui, Fredrik D. Johansson
2025	J	`jnl`	When are radiology reports useful for training medical image classifiers? CoRR Herman Bergström, Zhongqi Yue, Fredrik D. Johansson
2024	J	`jnl`	Active Preference Learning for Ordering Items In- and Out-of-sample. CoRR Herman Bergström, Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2024	A*	`conf`	Active preference learning for ordering items in- and out-of-sample. NeurIPS Herman Bergström, Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2024	J	`jnl`	Expert Study on Interpretable Machine Learning Models with Missing Data. CoRR Lena Stempfle, Arthur James, Julie Josse, Tobias Gauss, Fredrik D. Johansson
2024	—	`conf`	How Should We Represent History in Interpretable Models of Clinical Policies? ML4H@NeurIPS Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin, Heather J. Litman, Fredrik D. Johansson
2024	J	`jnl`	How Should We Represent History in Interpretable Models of Clinical Policies? CoRR Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin, Heather J. Litman, Fredrik D. Johansson
2024	J	`jnl`	Identifiable latent bandits: Combining observational data and exploration for personalized healthcare. CoRR Ahmet Zahid Balcioglu, Emil Carlsson, Fredrik D. Johansson
2024	A*	`conf`	IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark. NeurIPS Fredrik D. Johansson
2024	J	`jnl`	IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark. CoRR Fredrik D. Johansson
2024	A	`conf`	MINTY: Rule-based models that minimize the need for imputing features with missing values. AISTATS Lena Stempfle, Fredrik D. Johansson
2024	J	`jnl`	Overcoming label shift in targeted federated learning. CoRR Edvin Listo Zec, Adam Breitholtz, Fredrik D. Johansson
2024	A	`conf`	Pure Exploration in Bandits with Linear Constraints. AISTATS Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi
2024	J	`jnl`	Unsupervised Domain Adaptation by Learning Using Privileged Information. Trans. Mach. Learn. Res. Adam Breitholtz, Anton Matsson, Fredrik D. Johansson
2023	J	`jnl`	Fast Treatment Personalization with Latent Bandits in Fixed-Confidence Pure Exploration. Trans. Mach. Learn. Res. Newton Mwai Kinyanjui, Emil Carlsson, Fredrik D. Johansson
2023	J	`jnl`	Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities. CoRR Connor T. Jerzak, Fredrik D. Johansson, Adel Daoud
2023	J	`jnl`	MINTY: Rule-based Models that Minimize the Need for Imputing Features with Missing Values. CoRR Lena Stempfle, Fredrik D. Johansson
2023	J	`jnl`	Off-Policy Evaluation with Out-of-Sample Guarantees. Trans. Mach. Learn. Res. Sofia Ek, Dave Zachariah, Fredrik D. Johansson, Peter Stoica
2023	J	`jnl`	Practicality of generalization guarantees for unsupervised domain adaptation with neural networks. CoRR Adam Breitholtz, Fredrik D. Johansson
2023	J	`jnl`	Pure Exploration in Bandits with Linear Constraints. CoRR Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi
2023	A*	`conf`	Sharing Pattern Submodels for Prediction with Missing Values. AAAI Lena Stempfle, Ashkan Panahi, Fredrik D. Johansson
2023	A*	`conf`	Time Series of Satellite Imagery Improve Deep Learning Estimates of Neighborhood-Level Poverty in Africa. IJCAI Markus B. Pettersson, Mohammad Kakooei, Julia Ortheden, Fredrik D. Johansson, Adel Daoud
2023	J	`jnl`	Unsupervised domain adaptation by learning using privileged information. CoRR Adam Breitholtz, Anton Matsson, Fredrik D. Johansson
2022	—	`conf`	ADCB: An Alzheimer's disease simulator for benchmarking observational estimators of causal effects. CHIL Newton Mwai Kinyanjui, Fredrik D. Johansson
2022	A	`conf`	Case-based off-policy evaluation using prototype learning. UAI Anton Matsson, Fredrik D. Johansson
2022	A*	`conf`	Efficient learning of nonlinear prediction models with time-series privileged information. NeurIPS Bastian Jung, Fredrik D. Johansson
2022	J	`jnl`	Efficient learning of nonlinear prediction models with time-series privileged information. CoRR Bastian Jung, Fredrik D. Johansson
2022	J	`jnl`	Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects. J. Mach. Learn. Res. Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David A. Sontag
2022	J	`jnl`	Practicality of generalization guarantees for unsupervised domain adaptation with neural networks. Trans. Mach. Learn. Res. Adam Breitholtz, Fredrik D. Johansson
2022	J	`jnl`	Sharing pattern submodels for prediction with missing values. CoRR Lena Stempfle, Fredrik D. Johansson
2022	J	`jnl`	Using satellites and artificial intelligence to measure health and material-living standards in India. CoRR Adel Daoud, Felipe Jordan, Makkunda Sharma, Fredrik D. Johansson, Devdatt P. Dubhashi, Sourabh Bikash Paul, Subhashis Banerjee
2021	J	`jnl`	ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects. CoRR Newton Mwai Kinyanjui, Fredrik D. Johansson
2021	J	`jnl`	Case-based off-policy policy evaluation using prototype learning. CoRR Anton Matsson, Fredrik D. Johansson
2021	B	`conf`	Learning Approximate and Exact Numeral Systems via Reinforcement Learning. CogSci Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2021	J	`jnl`	Learning Approximate and Exact Numeral Systems via Reinforcement Learning. CoRR Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2021	A*	`conf`	Thompson Sampling for Bandits with Clustered Arms. IJCAI Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2021	J	`jnl`	Thompson Sampling for Bandits with Clustered Arms. CoRR Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson
2021	J	`jnl`	Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models. CoRR Rickard Karlsson, Martin Willbo, Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag, Fredrik D. Johansson
2020	J	`jnl`	A survey on graph kernels. Appl. Netw. Sci. Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2020	A	`conf`	Characterization of Overlap in Observational Studies. AISTATS Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney
2020	A*	`conf`	Estimation of Bounds on Potential Outcomes For Decision Making. ICML Maggie Makar, Fredrik D. Johansson, John V. Guttag, David A. Sontag
2020	J	`jnl`	Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects. CoRR Fredrik D. Johansson, Uri Shalit, Nathan Kallus, David A. Sontag
2020	A*	`conf`	Learning to search efficiently for causally near-optimal treatments. NeurIPS Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson
2020	J	`jnl`	Learning to search efficiently for causally near-optimal treatments. CoRR Samuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson
2019	J	`jnl`	A Survey on Graph Kernels. CoRR Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2019	J	`jnl`	Characterization of Overlap in Observational Studies. CoRR Fredrik D. Johansson, Dennis Wei, Michael Oberst, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney
2019	J	`jnl`	Estimation of Utility-Maximizing Bounds on Potential Outcomes. CoRR Maggie Makar, Fredrik D. Johansson, John V. Guttag, David A. Sontag
2019	A	`conf`	Support and Invertibility in Domain-Invariant Representations. AISTATS Fredrik D. Johansson, David A. Sontag, Rajesh Ranganath
2019	J	`jnl`	Support and Invertibility in Domain-Invariant Representations. CoRR Fredrik D. Johansson, David A. Sontag, Rajesh Ranganath
2018	J	`jnl`	Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR 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
2018	J	`jnl`	Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions. CoRR Fredrik D. Johansson
2018	A*	`conf`	Why Is My Classifier Discriminatory? NeurIPS Irene Y. Chen, Fredrik D. Johansson, David A. Sontag
2018	J	`jnl`	Why Is My Classifier Discriminatory? CoRR Irene Y. Chen, Fredrik D. Johansson, David A. Sontag
2017	A*	`conf`	Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery. ICML Ashkan Panahi, Devdatt P. Dubhashi, Fredrik D. Johansson, Chiranjib Bhattacharyya
2017	A*	`conf`	Estimating individual treatment effect: generalization bounds and algorithms. ICML Uri Shalit, Fredrik D. Johansson, David A. Sontag
2016	J	`jnl`	Bounding and Minimizing Counterfactual Error. CoRR Uri Shalit, Fredrik D. Johansson, David A. Sontag
2016	A*	`conf`	Learning Representations for Counterfactual Inference. ICML Fredrik D. Johansson, Uri Shalit, David A. Sontag
2016	J	`jnl`	Learning Representations for Counterfactual Inference. CoRR Fredrik D. Johansson, Uri Shalit, David A. Sontag
2015	B	`conf`	Classifying Large Graphs with Differential Privacy. MDAI Fredrik D. Johansson, Otto Frost, Carl Retzner, Devdatt P. Dubhashi
2015	B	`conf`	Generalized Shortest Path Kernel on Graphs. Discovery Science Linus Hermansson, Fredrik D. Johansson, Osamu Watanabe
2015	J	`jnl`	Generalized Shortest Path Kernel on Graphs. CoRR Linus Hermansson, Fredrik D. Johansson, Osamu Watanabe
2015	A*	`conf`	Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings. KDD Fredrik D. Johansson, Devdatt P. Dubhashi
2015	—	`conf`	Neural context embeddings for automatic discovery of word senses. VS@HLT-NAACL Mikael Kågebäck, Fredrik D. Johansson, Richard Johansson, Devdatt P. Dubhashi
2015	J	`jnl`	Visions and open challenges for a knowledge-based culturomics. Int. J. Digit. Libr. 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
2015	—	`conf`	Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization. NIPS Fredrik D. Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt P. Dubhashi
2014	A*	`conf`	Global graph kernels using geometric embeddings. ICML Fredrik D. Johansson, Vinay Jethava, Devdatt P. Dubhashi, Chiranjib Bhattacharyya