Publications by Christos Dimitrakakis

DUCT: An Upper Confidence Bound Approach to Distributed Constraint Optimization Problems

Boi Faltings, Christos Dimitrakakis, Brammert Ottens

We propose a distributed upper confidence bound approach, DUCT, for solving distributed constraint optimization problems. We compare four variants of this approach with a baseline random sampling algorithm, as well as other complete and incomplete algorith ...

Assoc Computing Machinery2017

Expected Loss Analysis for Authentication in Constrained Channels

Serge Vaudenay, Christos Dimitrakakis, Aikaterini Mitrokotsa

We derive bounds on the expected loss for authentication protocols in channels which are constrained due to noisy conditions and communication costs. This is motivated by a number of authentication protocols, where at least some part of the authentication ...

IOS Press2015

On Selecting the Nonce Length in Distance-Bounding Protocols

Serge Vaudenay, Christos Dimitrakakis, Aikaterini Mitrokotsa

Distance-bounding protocols form a family of challenge-response authentication protocols that have been introduced to thwart relay attacks. They enable a verifier to authenticate and to establish an upper bound on the physical distance to an untrusted prov ...

Oxford University Press2013

Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex

Christos Dimitrakakis

The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strength ...

Public Library Science2013

Intrusion Detection in MANET Using Classification Algorithms: The Effects of Cost and Model Selection

Christos Dimitrakakis, Aikaterini Mitrokotsa

Intrusion detection is frequently used as a second line of defense in Mobile Ad-hoc Networks (MANETs). In this paper we examine how to properly use classification methods in intrusion detection for MANETs. In order to do so we evaluate five supervised clas ...

Elsevier2013

Personalized News Recommendation with Context Trees

Boi Faltings, Christos Dimitrakakis, Florent Frédéric Garcin

The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...

2013

Probabilistic inverse reinforcement learning in unknown environments

Christos Dimitrakakis

We consider the problem of learning by demonstration from agents acting in unknown stochastic Markov environments or games. Our aim is to estimate agent preferences in order to construct improved policies for the same task that the agents are trying to sol ...

2013

Linear Bayesian Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis

This paper proposes a simple linear Bayesian approach to reinforcement learning. We show that with an appropriate basis, a Bayesian linear Gaussian model is sufficient for accurately estimating the system dynamics, and in particular when we allow for corre ...

2013

DUCT: An upper confidence bound approach to distributed constraint optimization problems

Boi Faltings, Christos Dimitrakakis, Brammert Ottens

The Upper Confidence Bounds (UCB) algorithm is a well-known near-optimal strategy for the stochastic multi-armed bandit problem. Its extensions to trees, such as the Upper Confidence Tree (UCT) algorithm, have resulted in good solutions to the problem of G ...

2012

Expected loss bounds for authentication in constrained channels

Serge Vaudenay, Christos Dimitrakakis, Aikaterini Mitrokotsa

We derive bounds on the expected loss for authenti-cation protocols in channels which are constrained due to noisyconditions and communication costs. This is motivated by anumber of authentication protocols, where at least some partof the authentication is ...

Ieee2012