Person

Christos Dimitrakakis

This person is no longer with EPFL

Related publications (50)

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

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

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

Robust and Private Bayesian Inference

Christos Dimitrakakis, Aikaterini Mitrokotsa

We examine the robustness and privacy properties of Bayesian inference under assumptions on the prior, but without any modifications to the Bayesian framework. First, we generalise the concept of differential privacy to arbitrary dataset distances, outcome ...

2013

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 ...

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

Sparse reward processes

Christos Dimitrakakis

We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is a relation among those tasks, then the information gained during execution of one task has value for the execution of another task. Cons ...

arxiv2012

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

Preference elicitation and inverse reinforcement learning

Christos Dimitrakakis

We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous work on Bayesian inverse reinforcement learning and allows us to obtain a pos ...

2011

Robust Bayesian reinforcement learning through tight lower bounds

Christos Dimitrakakis

In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinforcement learning problems. While utility bounds are known to exist for this ...

2011

Bayesian multitask inverse reinforcement learning

Christos Dimitrakakis

We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or as different experts trying to solve the same task. Our main contribution is ...

2011

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