Deep Gamblers: Learning to Abstain with Portfolio Theory

29 June 2019

Louis-Philippe Morency

Masahito Ueda

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Papers citing "Deep Gamblers: Learning to Abstain with Portfolio Theory"

31 / 31 papers shown

Title
Variational Visual Question Answering Tobias Jan Wieczorek Nathalie Daun Mohammad Emtiyaz Khan Marcus Rohrbach OOD 44 0 0 14 May 2025
Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes Yuanpeng Tu Yuxi Li Boshen Zhang Liang Liu Jun Zhang Yue Wang C. Zhao 61 3 0 03 Jan 2025
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 25 5 0 09 Feb 2024
Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention Anqi Mao M. Mohri Yutao Zhong 32 22 0 23 Oct 2023
Learning to Abstain From Uninformative Data Yikai Zhang Songzhu Zheng M. Dalirrooyfard Pengxiang Wu Anderson Schneider Anant Raj Yuriy Nevmyvaka Chao Chen 26 2 0 25 Sep 2023
Training Private Models That Know What They Don't Know Stephan Rabanser Anvith Thudi Abhradeep Thakurta Krishnamurthy Dvijotham Nicolas Papernot 26 7 0 28 May 2023
Energy-based Detection of Adverse Weather Effects in LiDAR Data Aldi Piroli Vinzenz Dallabetta Johannes Kopp M. Walessa D. Meissner Klaus C. J. Dietmayer 30 17 0 25 May 2023
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing M. Hasan Moloud Abdar Abbas Khosravi U. Aickelin Pietro Lio Ibrahim Hossain Ashikur Rahman Saeid Nahavandi 37 4 0 11 Apr 2023
Affinity Uncertainty-based Hard Negative Mining in Graph Contrastive Learning Chaoxi Niu Guansong Pang Ling-Hao Chen 24 9 0 31 Jan 2023
A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification Paul F. Jaeger Carsten T. Lüth Lukas Klein Till J. Bungert UQCV 30 35 0 28 Nov 2022
Gumbel-Softmax Selective Networks Mahmoud Salem Mohamed Osama Ahmed Frederick Tung Gabriel L. Oliveira 19 1 0 19 Nov 2022
AUC-based Selective Classification Andrea Pugnana Salvatore Ruggieri 26 9 0 19 Oct 2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 34 80 0 05 Oct 2022
MaskTune: Mitigating Spurious Correlations by Forcing to Explore Saeid Asgari Taghanaki Aliasghar Khani Fereshte Khani A. Gholami Linh-Tam Tran Ali Mahdavi-Amiri Ghassan Hamarneh AAML 46 45 0 30 Sep 2022
Selective Classification Via Neural Network Training Dynamics Stephan Rabanser Anvith Thudi Kimia Hamidieh Adam Dziedzic Nicolas Papernot 29 21 0 26 May 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder Yaniv Romano Matteo Sesia Yanfei Zhou UQCV 31 49 0 12 May 2022
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning Paul Pu Liang Yiwei Lyu Xiang Fan Zetian Wu Yun Cheng ... Peter Wu Michelle A. Lee Yuke Zhu Ruslan Salakhutdinov Louis-Philippe Morency VLM 32 159 0 15 Jul 2021
Learning to Complete Code with Sketches Daya Guo Alexey Svyatkovskiy Jian Yin Nan Duan Marc Brockschmidt Miltiadis Allamanis 21 40 0 18 Jun 2021
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction Liu Ziyin Kentaro Minami Kentaro Imajo 29 4 0 08 Jun 2021
Differentiable Learning Under Triage Nastaran Okati A. De Manuel Gomez Rodriguez 38 63 0 16 Mar 2021
An Investigation of how Label Smoothing Affects Generalization Blair Chen Liu Ziyin Zihao Wang Paul Pu Liang UQCV 21 17 0 23 Oct 2020
Classification with Rejection Based on Cost-sensitive Classification Nontawat Charoenphakdee Zhenghang Cui Yivan Zhang Masashi Sugiyama 80 64 0 22 Oct 2020
Classification Under Human Assistance A. De Nastaran Okati Ali Zarezade Manuel Gomez Rodriguez 16 49 0 21 Jun 2020
SoQal: Selective Oracle Questioning in Active Learning Dani Kiyasseh T. Zhu David Clifton 30 0 0 22 Apr 2020
Learning Not to Learn in the Presence of Noisy Labels Liu Ziyin Blair Chen Ru Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda NoLa 26 18 0 16 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 22 89 0 11 Feb 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 87 1,355 0 21 Oct 2019
Regression Under Human Assistance A. De Nastaran Okati Paramita Koley Niloy Ganguly Manuel Gomez Rodriguez 21 62 0 06 Sep 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,892 0 15 Sep 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015