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Nearly optimal exploration-exploitation decision thresholds

Publications associées (33)

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When Stuck, Flip a Coin

Slobodan Mitrovic

Many modern services need to routinely perform tasks on a large scale. This prompts us to consider the following question: How can we design efficient algorithms for large-scale computation? In this thesis, we focus on devising a general strategy to addr ...

EPFL2018

Asynchronous updates for stochastic gradient descent

Alberto Silvio Chiappa

Finding convergence rates for numerical optimization algorithms is an important task, because it gives a justification to their use in solving practical problems, while also providing a way to compare their efficiency. This is especially useful in an async ...

2017

From Acoustic Room Reconstruction to SLAM

Martin Vetterli, Ivan Dokmanic

Recent works on reconstruction of room geometry from echoes assume that the geometry of the sensor array is known. In this paper, we show that such an assumption is not essential; echoes provide sufficient clues to reconstruct the room’s and the array’s ge ...

Ieee2016

Centrality of trees for capacitated -center

Ola Nils Anders Svensson, Hyung Chan An, Aditya Bhaskara

We consider the capacitated -center problem. In this problem we are given a finite set of locations in a metric space and each location has an associated non-negative integer capacity. The goal is to choose (open) locations (called centers) and assign each ...

Springer Heidelberg2015

Source Localization and Tracking in Non-Convex Rooms

Martin Vetterli, Ivan Dokmanic, Orhan Öçal

We consider the estimation of the acoustic source position in a known room from recordings by a microphone array. We propose an algorithm that does not require the room to be convex, nor a line-of-sight path between the microphone array and the source to b ...

Ieee2014

Centrality of Trees for Capacitated k-Center

Ola Nils Anders Svensson, Hyung Chan An, Aditya Bhaskara

We consider the capacitated k-center problem. In this problem we are given a finite set of locations in a metric space and each location has an associated non-negative integer capacity. The goal is to choose (open) k locations (called centers) and assign e ...

Springer2014

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

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012

Knowledge-based design space exploration of wireless sensor networks

David Atienza Alonso, Ivan Beretta

The complexity of Wireless Sensor Networks (WSNs) has been constantly increasing over the last decade, and the necessity of efficient CAD tools has been growing accordingly. In fact, the size of the design space of a WSN has become large, and an exploratio ...

ACM Press2012

Vector Network Coding

Christina Fragouli, Javad Ebrahimi Boroojeni

We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying th ...

2010