On the Sample Complexity of Representation Learning in Multi-task Bandits with Global and Local structure
We investigate the sample complexity of learning the optimal arm for multi-task bandit problems. Arms consist of two components: one that is shared across tasks (that we call representation) and...
From self-tuning regulators to reinforcement learning and back again
Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include self-driving...
Learning to Personalize in Appearance-Based Gaze Tracking
Personal variations severely limit the performance of appearance-based gaze tracking. Adapting to these variations using standard neural network model adaptation methods is difficult. The problems...
Clustering in Block Markov Chains
This paper considers cluster detection in Block Markov Chains (BMCs). These Markov chains are characterized by a block structure in their transition matrix. More precisely, the $n$ possible states...
Accurate Community Detection in the Stochastic Block Model via Spectral Algorithms
We consider the problem of community detection in the Stochastic Block Model with a finite number $K$ of communities of sizes linearly growing with the network size $n$. This model consists in a...
Cluster-Aided Mobility Predictions
Predicting the future location of users in wireless net- works has numerous applications, and can help service providers to improve the quality of service perceived by their clients. The location...
Streaming, Memory Limited Algorithms for Community Detection
In this paper, we consider sparse networks consisting of a finite number of non-overlapping communities, i.e. disjoint clusters, so that there is higher density within clusters than across...
Emergent Behaviors over Signed Random Dynamical Networks: Relative-State-Flipping Model
We study asymptotic dynamical patterns that emerge among a set of nodes interacting in a dynamically evolving signed random network, where positive links carry out standard consensus and negative...
Spectrum Bandit Optimization
We consider the problem of allocating radio channels to links in a wireless network. Links interact through interference, modelled as a conflict graph (i.e., two interfering links cannot be...
Distributed Load Balancing in Heterogeneous Systems
We consider the problem of distributed load balancing in heterogenous parallel server systems, where the service rate achieved by a user at a server depends on both the user and the server. Such...