Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

26 February 2018

Papers citing "Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling"

50 / 227 papers shown

Title
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 37 1,877 0 12 Nov 2020
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations? Chaoqi Wang Shengyang Sun Roger C. Grosse UQCV 6 24 0 06 Nov 2020
Dynamically Throttleable Neural Networks (TNN) Hengyue Liu Samyak Parajuli Jesse Hostetler S. Chai B. Bhanu 6 4 0 01 Nov 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 23 83 0 28 Oct 2020
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures Benjamin Kompa Jasper Snoek Andrew L. Beam UQCV BDL 26 29 0 06 Oct 2020
Neural Thompson Sampling Weitong Zhang Dongruo Zhou Lihong Li Quanquan Gu 18 114 0 02 Oct 2020
Uncertainty Sets for Image Classifiers using Conformal Prediction Anastasios Nikolas Angelopoulos Stephen Bates Jitendra Malik Michael I. Jordan UQCV 17 315 0 29 Sep 2020
VacSIM: Learning Effective Strategies for COVID-19 Vaccine Distribution using Reinforcement Learning R. Awasthi K. K. Guliani Saif Ahmad Khan Aniket Vashishtha M. S. Gill Arshita Bhatt A. Nagori Aniket Gupta Ponnurangam Kumaraguru Tavpritesh Sethi 24 24 0 14 Sep 2020
$β$ -Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers Dionysis Manousakas Cecilia Mascolo 17 2 0 31 Aug 2020
A Survey on Assessing the Generalization Envelope of Deep Neural Networks: Predictive Uncertainty, Out-of-distribution and Adversarial Samples Julia Lust A. P. Condurache UQCV AAML AI4CE 13 7 0 21 Aug 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations Dalin Guo S. Ktena Ferenc Huszár Pranay K. Myana Wenzhe Shi Alykhan Tejani OffRL 17 39 0 03 Aug 2020
Greedy Bandits with Sampled Context Dom Huh 9 0 0 27 Jul 2020
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty Théo Guénais Dimitris Vamvourellis Yaniv Yacoby Finale Doshi-Velez Weiwei Pan UQCV 6 13 0 12 Jul 2020
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems Tong Yu B. Kveton Zheng Wen Ruiyi Zhang Ole J. Mengshoel TDI 11 2 0 09 Jul 2020
Recurrent Neural-Linear Posterior Sampling for Nonstationary Contextual Bandits Aditya A. Ramesh Paulo E. Rauber Michelangelo Conserva Jürgen Schmidhuber 12 0 0 09 Jul 2020
Hedging using reinforcement learning: Contextual $k$ -Armed Bandit versus $Q$ -learning Loris Cannelli Giuseppe Nuti M. Sala O. Szehr OffRL 16 9 0 03 Jul 2020
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift Alex J. Chan Ahmed Alaa Zhaozhi Qian M. Schaar UQCV BDL OOD 12 38 0 26 Jun 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 25 4 0 21 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 11 436 0 17 Jun 2020
TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation Jackie Baek Vivek F. Farias 22 9 0 11 Jun 2020
Gaussian Gated Linear Networks David Budden Adam H. Marblestone Eren Sezener Tor Lattimore Greg Wayne J. Veness BDL AI4CE 14 12 0 10 Jun 2020
Meta-Learning Bandit Policies by Gradient Ascent B. Kveton Martin Mladenov Chih-Wei Hsu Manzil Zaheer Csaba Szepesvári Craig Boutilier 35 9 0 09 Jun 2020
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling Qin Ding Cho-Jui Hsieh James Sharpnack 17 37 0 07 Jun 2020
A Linear Bandit for Seasonal Environments Giuseppe Di Benedetto Vito Bellini Giovanni Zappella 18 7 0 28 Apr 2020
Deep Reinforcement Learning with Weighted Q-Learning Andrea Cini Carlo DÉramo Jan Peters C. Alippi OffRL 16 9 0 20 Mar 2020
Self-Supervised Contextual Bandits in Computer Vision A. Deshmukh Abhimanu Kumar Levi Boyles Denis Xavier Charles Eren Manavoglu Ürün Dogan SSL 23 3 0 18 Mar 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 172 758 0 13 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 25 277 0 24 Feb 2020
On Thompson Sampling with Langevin Algorithms Eric Mazumdar Aldo Pacchiano Yi-An Ma Peter L. Bartlett Michael I. Jordan 6 11 0 23 Feb 2020
Online Learning in Contextual Bandits using Gated Linear Networks Eren Sezener Marcus Hutter David Budden Jianan Wang J. Veness 4 8 0 21 Feb 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples Mao Ye Tongzheng Ren Qiang Liu 18 8 0 21 Feb 2020
Bayesian Meta-Prior Learning Using Empirical Bayes Sareh Nabi Houssam Nassif Joseph Hong H. Mamani Guido Imbens 14 18 0 04 Feb 2020
Machine learning based co-creative design framework Brian Quanz Wei-Ling Sun Ajay A. Deshpande Dhruv Shah Jae-eun Park HAI 9 9 0 23 Jan 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N. Brosse C. Riquelme Alice Martin Sylvain Gelly Eric Moulines BDL OOD UQCV 11 33 0 22 Jan 2020
Incentivising Exploration and Recommendations for Contextual Bandits with Payments Priyank Agrawal Theja Tulabandhula OffRL 12 4 0 22 Jan 2020
Continuous Meta-Learning without Tasks James Harrison Apoorva Sharma Chelsea Finn Marco Pavone CLL OOD 14 79 0 18 Dec 2019
Benchmarking the Neural Linear Model for Regression Sebastian W. Ober C. Rasmussen BDL 11 41 0 18 Dec 2019
Bayesian Linear Regression on Deep Representations J. Moberg Lennart Svensson Juliano Pinto H. Wymeersch BDL UQCV 11 2 0 14 Dec 2019
Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging J. Zech Jessica Zosa Forde Michael L. Littman 13 5 0 08 Dec 2019
A Biologically Plausible Benchmark for Contextual Bandit Algorithms in Precision Oncology Using in vitro Data Niklas Rindtorff Mingyu Lu Nisarg A. Patel Huahua Zheng Alexander DÁmour 9 5 0 11 Nov 2019
Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints Sam Daulton Shaun Singh Vashist Avadhanula Drew Dimmery E. Bakshy 13 13 0 02 Nov 2019
Thompson Sampling via Local Uncertainty Zhendong Wang Mingyuan Zhou 16 18 0 30 Oct 2019
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems Sharan Vaswani Abbas Mehrabian A. Durand B. Kveton 6 26 0 11 Oct 2019
AutoML for Contextual Bandits Praneet Dutta Man Kit Cheuk Jonathan S Kim M. Mascaro OffRL 11 6 0 07 Sep 2019
PHYRE: A New Benchmark for Physical Reasoning A. Bakhtin L. V. D. van der Maaten Justin Johnson Laura Gustafson Ross B. Girshick LRM 14 121 0 15 Aug 2019
Thompson Sampling with Approximate Inference My Phan Yasin Abbasi-Yadkori Justin Domke 8 28 0 14 Aug 2019
Vector Quantized Bayesian Neural Network Inference for Data Streams Namuk Park Taekyu Lee Songkuk Kim MQ 17 9 0 12 Jul 2019
Ín-Between' Uncertainty in Bayesian Neural Networks Andrew Y. K. Foong Yingzhen Li José Miguel Hernández-Lobato Richard E. Turner BDL UQCV 24 116 0 27 Jun 2019
Randomized Exploration in Generalized Linear Bandits B. Kveton Manzil Zaheer Csaba Szepesvári Lihong Li Mohammad Ghavamzadeh Craig Boutilier 9 95 0 21 Jun 2019