Jonas Mueller

According to our database, Jonas Mueller authored at least 49 papers between 2015 and 2024.

Collaborative distances:

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

2024

Automated Data Curation for Robust Language Model Fine-Tuning.

Jiuhai Chen, Jonas Mueller

CoRR, 2024

2023

Flexible Model Aggregation for Quantile Regression.

Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani

J. Mach. Learn. Res., 2023

ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data.

Ulyana Tkachenko, Aditya Thyagarajan, Jonas Mueller

CoRR, 2023

Quantifying Uncertainty in Answers from any Language Model via Intrinsic and Extrinsic Confidence Assessment.

Jiuhai Chen, Jonas Mueller

CoRR, 2023

Estimating label quality and errors in semantic segmentation data via any model.

Vedang Lad, Jonas Mueller

CoRR, 2023

Detecting Errors in Numerical Data via any Regression Model.

Hang Zhou, Jonas Mueller, Mayank Kumar, Jane-Ling Wang, Jing Lei

CoRR, 2023

Detecting Dataset Drift and Non-IID Sampling via k-Nearest Neighbors.

Jesse Cummings, Elías Snorrason, Jonas Mueller

CoRR, 2023

ActiveLab: Active Learning with Re-Labeling by Multiple Annotators.

Hui Wen Goh, Jonas Mueller

CoRR, 2023

DataPerf: Benchmarks for Data-Centric AI Development.

Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges.

Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Identifying Incorrect Annotations in Multi-Label Classification Data.

Aditya Thyagarajan, Elías Snorrason, Curtis G. Northcutt, Jonas Mueller

CoRR, 2022

Utilizing supervised models to infer consensus labels and their quality from data with multiple annotators.

Hui Wen Goh, Ulyana Tkachenko, Jonas Mueller

CoRR, 2022

Detecting Label Errors in Token Classification Data.

Wei-Chen Wang, Jonas Mueller

CoRR, 2022

Data drift correction via time-varying importance weight estimator.

Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola

CoRR, 2022

DataPerf: Benchmarks for Data-Centric AI Development.

Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi

CoRR, 2022

Back to the Basics: Revisiting Out-of-Distribution Detection Baselines.

Johnson Kuan, Jonas Mueller

CoRR, 2022

A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features.

Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf

CoRR, 2022

Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline.

Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor

CoRR, 2022

Adaptive Interest for Emphatic Reinforcement Learning.

Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola

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

Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.

Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf

Proceedings of the Tenth International Conference on Learning Representations, 2022

ResNeSt: Split-Attention Networks.

Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features.

Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf

CoRR, 2021

Deep Quantile Aggregation.

Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani

CoRR, 2021

Continuous Doubly Constrained Batch Reinforcement Learning.

Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola

CoRR, 2021

Deep Extended Hazard Models for Survival Analysis.

Qixian Zhong, Jonas Mueller, Jane-Ling Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks.

Curtis G. Northcutt, Anish Athalye, Jonas Mueller

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Continuous Doubly Constrained Batch Reinforcement Learning.

Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Overinterpretation reveals image classification model pathologies.

Brandon Carter, Siddhartha Jain, Jonas Mueller, David Gifford

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Learning for Functional Data Analysis with Adaptive Basis Layers.

Junwen Yao, Jonas Mueller, Jane-Ling Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing.

Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis

Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, 2021

2020

TraDE: Transformers for Density Estimation.

Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola

CoRR, 2020

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola

CoRR, 2020

Antibody complementarity determining region design using high-capacity machine learning.

Ge Liu, Haoyang Zeng, Jonas Mueller, Brandon Carter, Ziheng Wang, Jonas Schilz, Geraldine Horny, Michael E. Birnbaum, Stefan Ewert, David K. Gifford

Bioinform., 2020

Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation.

Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola

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

Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data.

Jonas Mueller, Xingjian Shi, Alexander J. Smola

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Educating Text Autoencoders: Latent Representation Guidance via Denoising.

Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi S. Jaakkola

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

Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles.

Siddhartha Jain, Ge Liu, Jonas Mueller, David Gifford

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Latent Space Secrets of Denoising Text-Autoencoders.

Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi S. Jaakkola

CoRR, 2019

Unsupervised Text Style Transfer via Iterative Matching and Translation.

Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus

CoRR, 2019

Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing.

Jonas Mueller, Vasilis Syrgkanis, Matt Taddy

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Recognizing Variables from Their Data via Deep Embeddings of Distributions.

Jonas Mueller, Alex Smola

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation.

Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

What made you do this? Understanding black-box decisions with sufficient input subsets.

Brandon Carter, Jonas Mueller, Siddhartha Jain, David K. Gifford

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

2018

Flexible models for understanding and optimizing complex populations.

Jonas Mueller

PhD thesis, 2018

2017

Sequence to Better Sequence: Continuous Revision of Combinatorial Structures.

Jonas Mueller, David K. Gifford, Tommi S. Jaakkola

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

Learning Optimal Interventions.

Jonas Mueller, David Reshef, George Du, Tommi S. Jaakkola

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Siamese Recurrent Architectures for Learning Sentence Similarity.

Jonas Mueller, Aditya Thyagarajan

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Principal Differences Analysis: Interpretable Characterization of Differences between Distributions.

Jonas Mueller, Tommi S. Jaakkola

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