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Jean-Francois Ton
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2020 – today
- 2024
- [c15]Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu:
Fair Classifiers that Abstain without Harm. ICLR 2024 - [c14]Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu:
Conformal Counterfactual Inference under Hidden Confounding. KDD 2024: 397-408 - [i20]Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton, Hongyi Guo, Andrew Estornell, Yang Liu:
Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting. CoRR abs/2402.10412 (2024) - [i19]Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu:
Dataset Fairness: Achievable Fairness on Your Data With Utility Guarantees. CoRR abs/2402.17106 (2024) - [i18]Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu:
Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation. CoRR abs/2403.05171 (2024) - [i17]Zonghao Chen, Ruocheng Guo, Jean-François Ton, Yang Liu:
Conformal Counterfactual Inference under Hidden Confounding. CoRR abs/2405.12387 (2024) - 2023
- [c13]Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton:
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. NeurIPS 2023 - [c12]Mengyue Yang, Yonggang Zhang, Zhen Fang, Yali Du, Furui Liu, Jean-Francois Ton, Jianhong Wang, Jun Wang:
Invariant Learning via Probability of Sufficient and Necessary Causes. NeurIPS 2023 - [c11]Mengyue Yang, Jun Wang, Jean-Francois Ton:
Rectifying Unfairness in Recommendation Feedback Loop. SIGIR 2023: 28-37 - [i16]Ruocheng Guo, Jean-François Ton, Yang Liu:
Fair Learning to Rank with Distribution-free Risk Control. CoRR abs/2306.07188 (2023) - [i15]Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li:
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. CoRR abs/2308.05374 (2023) - [i14]Mengyue Yang, Zhen Fang, Yonggang Zhang, Yali Du, Furui Liu, Jean-Francois Ton, Jun Wang:
Invariant Learning via Probability of Sufficient and Necessary Causes. CoRR abs/2309.12559 (2023) - [i13]Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li:
Deep Concept Removal. CoRR abs/2310.05755 (2023) - [i12]Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu:
Fair Classifiers that Abstain without Harm. CoRR abs/2310.06205 (2023) - [i11]Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton:
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. CoRR abs/2312.01457 (2023) - 2022
- [c10]Xing Liu, Harrison Zhu, Jean-Francois Ton, George Wynne, Andrew B. Duncan:
Grassmann Stein Variational Gradient Descent. AISTATS 2022: 2002-2021 - [c9]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind:
Regularized Training of Nearest Neighbor Language Models. NAACL-HLT (Student Research Workshop) 2022: 25-30 - [c8]Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. NeurIPS 2022 - [i10]Xing Liu, Harrison Zhu, Jean-François Ton, George Wynne, Andrew B. Duncan:
Grassmann Stein Variational Gradient Descent. CoRR abs/2202.03297 (2022) - [i9]Muhammad Faaiz Taufiq, Jean-Francois Ton, Robert Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. CoRR abs/2206.04405 (2022) - 2021
- [j1]Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic:
Towards a Unified Analysis of Random Fourier Features. J. Mach. Learn. Res. 22: 108:1-108:51 (2021) - [c7]Jean-François Ton, Dino Sejdinovic, Kenji Fukumizu:
Meta Learning for Causal Direction. AAAI 2021: 9897-9905 - [c6]Jean-Francois Ton, Lucian Chan, Yee Whye Teh, Dino Sejdinovic:
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings. AISTATS 2021: 1099-1107 - [c5]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Robust Pruning at Initialization. ICLR 2021 - [c4]Siu Lun Chau, Jean-Francois Ton, Javier González, Yee Whye Teh, Dino Sejdinovic:
BayesIMP: Uncertainty Quantification for Causal Data Fusion. NeurIPS 2021: 3466-3477 - [i8]Siu Lun Chau, Jean-François Ton, Javier González, Yee Whye Teh, Dino Sejdinovic:
BayesIMP: Uncertainty Quantification for Causal Data Fusion. CoRR abs/2106.03477 (2021) - [i7]Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Josh M. Susskind:
Regularized Training of Nearest Neighbor Language Models. CoRR abs/2109.08249 (2021) - 2020
- [c3]Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam R. Kosiorek, Yee Whye Teh:
MetaFun: Meta-Learning with Iterative Functional Updates. ICML 2020: 10617-10627 - [i6]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Pruning untrained neural networks: Principles and Analysis. CoRR abs/2002.08797 (2020) - [i5]Jean-Francois Ton, Dino Sejdinovic, Kenji Fukumizu:
Meta Learning for Causal Direction. CoRR abs/2007.02809 (2020)
2010 – 2019
- 2019
- [c2]Henry Chai, Jean-Francois Ton, Michael A. Osborne, Roman Garnett:
Automated Model Selection with Bayesian Quadrature. ICML 2019: 931-940 - [c1]Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic:
Towards a Unified Analysis of Random Fourier Features. ICML 2019: 3905-3914 - [i4]Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne:
Automated Model Selection with Bayesian Quadrature. CoRR abs/1902.09724 (2019) - [i3]Jean-Francois Ton, Lucian Chan, Yee Whye Teh, Dino Sejdinovic:
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings. CoRR abs/1906.02236 (2019) - [i2]Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam R. Kosiorek, Yee Whye Teh:
MetaFun: Meta-Learning with Iterative Functional Updates. CoRR abs/1912.02738 (2019) - 2018
- [i1]Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic:
A Unified Analysis of Random Fourier Features. CoRR abs/1806.09178 (2018)
Coauthor Index
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last updated on 2024-09-13 00:42 CEST by the dblp team
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