This paper focuses on motion prediction for point cloud sequences in the...
We propose Grab-UCB, a graph-kernel multi-arms bandit algorithm to learn...
This work introduces MiDi, a diffusion model for jointly generating mole...
Various approaches have been developed to upper bound the generalization...
Generalization error boundaries are essential for comprehending how well...
This paper aims at bringing some light and understanding to the field of...
Counterfactual risk minimization is a framework for offline policy
optim...
A common assumption in semi-supervised learning is that the labeled,
unl...
This work focuses on enabling user-centric immersive systems, in which e...
We provide an information-theoretic analysis of the generalization abili...
Bounding the generalization error of a supervised learning algorithm is ...
In this paper, we propose an end-to-end learning network to predict futu...
Generalization error bounds are critical to understanding the performanc...
Generalization error bounds are critical to understanding the performanc...
The effective representation, processing, analysis, and visualization of...
Upper Confidence Bound (UCB) is arguably the most commonly used method f...
A major challenge in reinforcement learning (RL) is the design of agents...
We study contextual multi-armed bandit problems in the case of multiple
...
We provide a theoretical analysis of the representation learning problem...
In this work, we study value function approximation in reinforcement lea...
In Virtual Reality (VR) applications, understanding how users explore th...
In this work, we study recommendation systems modelled as contextual
mul...
We derive the sum-rate-distortion region for a generic number of success...
Multiview applications endow final users with the possibility to freely
...
In this work, we propose a new learning framework for optimising transmi...