Christos Dimitrakakis

Orcid: 0000-0002-5367-5189

According to our database1, Christos Dimitrakakis authored at least 93 papers between 2004 and 2024.

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Bibliography

2024
Eliciting Kemeny Rankings.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation.
CoRR, 2023

Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer.
CoRR, 2023

Approximate Inference for the Bayesian Fairness Framework.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Policy Fairness and Unknown Bias Dynamics in Sequential Allocations.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Minimax-Bayes Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Decision Making Under Uncertainty and Reinforcement Learning - Theory and Algorithms
Intelligent Systems Reference Library 223, Springer, ISBN: 978-3-031-07612-1, 2022

Environment Design for Inverse Reinforcement Learning.
CoRR, 2022

Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty.
CoRR, 2022

SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Simulating University Application Data for Fair Matchings.
Proceedings of the Nordic Artificial Intelligence Research and Development, 2022

Interactive Inverse Reinforcement Learning for Cooperative Games.
Proceedings of the International Conference on Machine Learning, 2022

On Meritocracy in Optimal Set Selection.
Proceedings of the Equity and Access in Algorithms, Mechanisms, and Optimization, 2022

2021
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling.
CoRR, 2021

Adaptive Belief Discretization for POMDP Planning.
CoRR, 2021

Fair Set Selection: Meritocracy and Social Welfare.
CoRR, 2021

2020
Inferential Induction: Joint Bayesian Estimation of MDPs and Value Functions.
CoRR, 2020

Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning.
Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

Epistemic Risk-Sensitive Reinforcement Learning.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandits: Algorithms and Regret Bounds.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Bayesian Reinforcement Learning via Deep, Sparse Sampling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Program for TPDP 2016.
J. Priv. Confidentiality, 2019

Near-optimal Reinforcement Learning using Bayesian Quantiles.
CoRR, 2019

Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games.
CoRR, 2019

Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities.
CoRR, 2019

Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost?
CoRR, 2019

Randomised Bayesian Least-Squares Policy Iteration.
CoRR, 2019

Deeper & Sparser Exploration.
CoRR, 2019

Bayesian optimization in ab initio nuclear physics.
CoRR, 2019

Privacy of Real-Time Pricing in Smart Grid.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Bayesian Fairness.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
VIVO: A secure, privacy-preserving, and real-time crowd-sensing framework for the Internet of Things.
Pervasive Mob. Comput., 2018

On The Differential Privacy of Thompson Sampling With Gaussian Prior.
CoRR, 2018

2017
DUCT: An Upper Confidence Bound Approach to Distributed Constraint Optimization Problems.
ACM Trans. Intell. Syst. Technol., 2017

Differential Privacy for Bayesian Inference through Posterior Sampling.
J. Mach. Learn. Res., 2017

Calibrated Fairness in Bandits.
CoRR, 2017

Learning to Match.
CoRR, 2017

Subjective fairness: Fairness is in the eye of the beholder.
CoRR, 2017

Near-optimal blacklisting.
Comput. Secur., 2017

Bayesian Inference for Least Squares Temporal Difference Regularization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Multi-View Decision Processes: The Helper-AI Problem.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Differentially Private Encryption Scheme.
Proceedings of the Information Security - 20th International Conference, 2017

Thompson Sampling for Stochastic Bandits with Graph Feedback.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Achieving Privacy in the Adversarial Multi-Armed Bandit.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
On the Differential Privacy of Bayesian Inference.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Algorithms for Differentially Private Multi-Armed Bandits.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Expected loss analysis for authentication in constrained channels.
J. Comput. Secur., 2015

Distance-Bounding Protocols: Are You Close Enough?
IEEE Secur. Priv., 2015


Workshop Summary of AISec'15: 2015 Workshop on Artificial Intelligent and Security.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

Optimal Advertisement Strategies for Small and Big Companies.
Proceedings of the e-Infrastructure and e-Services - 7th International Conference, 2015

2014
Cover tree Bayesian reinforcement learning.
J. Mach. Learn. Res., 2014

Generalised Entropy MDPs and Minimax Regret.
CoRR, 2014

The Reinforcement Learning Competition 2014.
AI Mag., 2014

On the Leakage of Information in Biometric Authentication.
Proceedings of the Progress in Cryptology - INDOCRYPT 2014, 2014

Workshop Summary of AISec'14: 2014 Workshop on Artificial Intelligent and Security.
Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, 2014

Robust and Private Bayesian Inference.
Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

2013
Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex.
PLoS Comput. Biol., 2013

Robust, Secure and Private Bayesian Inference.
CoRR, 2013

On Selecting the Nonce Length in Distance-Bounding Protocols.
Comput. J., 2013

Intrusion detection in MANET using classification algorithms: The effects of cost and model selection.
Ad Hoc Networks, 2013

Probabilistic inverse reinforcement learning in unknown environments.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Personalized news recommendation with context trees.
Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

Linear Bayesian Reinforcement Learning.
Proceedings of the IJCAI 2013, 2013

ABC Reinforcement Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

Monte-Carlo utility estimates for Bayesian reinforcement learning.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Summary/overview for artificial intelligence and security (AISec'13).
Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, 2013

Generalization and Interference in Human Motor Control.
Proceedings of the Computational and Robotic Models of the Hierarchical Organization of Behavior, 2013

2012
Guest Editors' Introduction: Special Section on Learning, Games, and Security.
IEEE Trans. Dependable Secur. Comput., 2012

Near-Optimal Node Blacklisting in Adversarial Networks
CoRR, 2012

Sparse Reward Processes
CoRR, 2012

Expected loss bounds for authentication in constrained channels.
Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

2011
Phoneme and Sentence-Level Ensembles for Speech Recognition.
EURASIP J. Audio Speech Music. Process., 2011

Preference Elicitation and Inverse Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Bayesian Multitask Inverse Reinforcement Learning.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Robust Bayesian Reinforcement Learning through Tight Lower Bounds.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

2010
Efficient Methods for Near-Optimal Sequential Decision Making under Uncertainty.
Proceedings of the Interactive Collaborative Information Systems, 2010

Bayesian variable order Markov models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Reid et al.'s distance bounding protocol and mafia fraud attacks over noisy channels.
IEEE Commun. Lett., 2010

Expected loss analysis of thresholded authentication protocols in noisy conditions
CoRR, 2010

Context models on sequences of covers
CoRR, 2010

Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning.
Proceedings of the ICAART 2010 - Proceedings of the International Conference on Agents and Artificial Intelligence, Volume 1, 2010

2009
Statistical Decision Making for Authentication and Intrusion Detection.
Proceedings of the International Conference on Machine Learning and Applications, 2009

2008
Rollout sampling approximate policy iteration.
Mach. Learn., 2008

Intrusion Detection Using Cost-Sensitive Classification
CoRR, 2008

Cost-Minimising Strategies for Data Labelling: Optimal Stopping and Active Learning.
Proceedings of the Foundations of Information and Knowledge Systems, 2008

Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

Tree Exploration for Bayesian RL Exploration.
Proceedings of the 2008 International Conferences on Computational Intelligence for Modelling, 2008

2006
Nearly Optimal Exploration-Exploitation Decision Thresholds.
Proceedings of the Artificial Neural Networks, 2006

2005
Online adaptive policies for ensemble classifiers.
Neurocomputing, 2005

Boosting word error rates.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Boosting HMMs with an application to speech recognition.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Online policy adaptation for ensemble classifiers.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004


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