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1802.09127
Cited By
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
International Conference on Learning Representations (ICLR), 2018
26 February 2018
C. Riquelme
George Tucker
Jasper Snoek
BDL
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Papers citing
"Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling"
50 / 231 papers shown
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Evolutionary Generative Optimization: Towards Fully Data-Driven Evolutionary Optimization via Generative Learning
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144
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01 Aug 2025
Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown
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254
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21 Jul 2025
Measurement-Aligned Sampling for Inverse Problem
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Rob Brekelmans
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271
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13 Jun 2025
Neural Logistic Bandits
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Exploring Pseudo-Token Approaches in Transformer Neural Processes
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179
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19 Apr 2025
Active Human Feedback Collection via Neural Contextual Dueling Bandits
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315
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16 Apr 2025
CAE: Repurposing the Critic as an Explorer in Deep Reinforcement Learning
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Siyuan Qi
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320
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NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis Prediction
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Raheem Beyah
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271
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20 Mar 2025
Exploring the Potential of Bilevel Optimization for Calibrating Neural Networks
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365
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267
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Active Learning for Direct Preference Optimization
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354
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Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
H. Bui
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Anqi Liu
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08 Nov 2024
PageRank Bandits for Link Prediction
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Jiaru Zou
Zihao Li
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Dongqi Fu
Jian Kang
Hanghang Tong
Jingrui He
329
14
0
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Online Posterior Sampling with a Diffusion Prior
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Branislav Kveton
Boris Oreshkin
Youngsuk Park
Aniket Deshmukh
Rui Song
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215
4
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04 Oct 2024
The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems
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Ana Fernández del Río
Ivan Nazarov
Enric Jané
Moiz Hassan
Aditya Rastogi
Dexian Tang
243
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24 Sep 2024
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Michael Brennan Leong
Paulo Saraiva
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Aditya Rastogi
Moiz Hassan
Dexian Tang
África Periánez
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216
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Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services
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Michael Brennan Leong
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Ivan Nazarov
Aditya Rastogi
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OffRL
166
6
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14 Aug 2024
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Lazola Makhupula
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Moeti Moleko
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Dexian Tang
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177
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Meta Clustering of Neural Bandits
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Tianxin Wei
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297
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AExGym: Benchmarks and Environments for Adaptive Experimentation
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280
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Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
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Henry Lam
Haofeng Zhang
387
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Graph Neural Thompson Sampling
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Arash A. Amini
363
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Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning
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Josiah P. Hanna
Qiaomin Xie
Robert D. Nowak
635
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A Bayesian Approach to Online Planning
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David Ben-Eli
Carmel Rabinovitz
Gabi Guetta
Liran Gispan
Guy Zohar
Aviv Tamar
173
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Position: Why We Must Rethink Empirical Research in Machine Learning
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Moritz Herrmann
F. J. D. Lange
Katharina Eggensperger
Giuseppe Casalicchio
Marcel Wever
Matthias Feurer
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253
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Online Personalizing White-box LLMs Generation with Neural Bandits
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Weeden Daniel
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159
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Uncertainty in Language Models: Assessment through Rank-Calibration
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Xinmeng Huang
Shuo Li
Mengxin Yu
Matteo Sesia
Hamed Hassani
Insup Lee
Osbert Bastani
Guang Cheng
240
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On the Importance of Uncertainty in Decision-Making with Large Language Models
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Lucas Maystre
Sina Ghiassian
K. Ciosek
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342
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359
124
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ε-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment
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Hao-Lun Hsu
Qitong Gao
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273
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Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation
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Jean-François Ton
Wei Shen
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168
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Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models
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Jihua Zhu
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Zhiqiang Tian
FedML
229
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26 Feb 2024
Diffusion Models Meet Contextual Bandits
Imad Aouali
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294
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15 Feb 2024
Predictive Churn with the Set of Good Models
J. Watson-Daniels
Flavio du Pin Calmon
Alexander DÁmour
Carol Xuan Long
David C. Parkes
Berk Ustun
317
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12 Feb 2024
LiRank: Industrial Large Scale Ranking Models at LinkedIn
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Fedor Borisyuk
Mingzhou Zhou
Qingquan Song
Sirou Zhu
B. Tiwana
...
Chen-Chen Jiang
Haichao Wei
Maneesh Varshney
Amol Ghoting
Souvik Ghosh
189
10
0
10 Feb 2024
Efficient Exploration for LLMs
Vikranth Dwaracherla
S. Asghari
Botao Hao
Benjamin Van Roy
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419
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Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Zeji Yi
Yunyue Wei
Chu Xin Cheng
Kaibo He
Yanan Sui
207
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A Bayesian Framework of Deep Reinforcement Learning for Joint O-RAN/MEC Orchestration
Fahri Wisnu Murti
Samad Ali
Matti Latva-aho
225
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26 Dec 2023
Risk-Aware Continuous Control with Neural Contextual Bandits
AAAI Conference on Artificial Intelligence (AAAI), 2023
J. Ayala-Romero
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Xavier Pérez Costa
179
4
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RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions
Easton K. Huch
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Madeline R Abbott
J. Golbus
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Walter Dempsey
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375
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Jason Ramapuram
Sinead Williamson
Dan Busbridge
Eeshan Gunesh Dhekane
Russ Webb
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212
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Bairu Hou
Yujian Liu
Kaizhi Qian
Jacob Andreas
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UD
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335
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Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
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Ming Yin
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Yu Wang
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304
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Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization
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Nikhil Behari
Edward Hughes
Edwin Zhang
Dheeraj M. Nagaraj
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Milind Tambe
279
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Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling
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Hamid R. Rabiee
OffRL
242
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Multi-fidelity climate model parameterization for better generalization and extrapolation
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Pierre Gentine
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250
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Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness
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Jiuhai Chen
Jonas W. Mueller
360
113
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30 Aug 2023
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