collaborators

9 papers

cs.NI2021

Meta-Reinforcement Learning via Buffering Graph Signatures for Live Video Streaming Events

Stefanos Antaris, Dimitrios Rafailidis, Sarunas Girdzijauskas

In this study, we present a meta-learning model to adapt the predictions of the network's capacity between viewers who participate in a live video streaming event. We propose the M…

cs.IR2021

Sequence Adaptation via Reinforcement Learning in Recommender Systems

Stefanos Antaris, Dimitrios Rafailidis

Accounting for the fact that users have different sequential patterns, the main drawback of state-of-the-art recommendation strategies is that a fixed sequence length of user-item…

cs.AI2021

A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming

Stefanos Antaris, Dimitrios Rafailidis, Sarunas Girdzijauskas

In this paper we present a deep graph reinforcement learning model to predict and improve the user experience during a live video streaming event, orchestrated by an agent/tracker.…

cs.AI2021

Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events

Stefanos Antaris, Dimitrios Rafailidis, Romina Arriaza

Nowadays, live video streaming events have become a mainstay in viewer's communication in large international enterprises. Provided that viewers are distributed worldwide, the main…

cs.IR2020

Adaptive Neural Architectures for Recommender Systems

Dimitrios Rafailidis, Stefanos Antaris

Deep learning has proved an effective means to capture the non-linear associations of user preferences. However, the main drawback of existing deep learning architectures is that t…

cs.LG2020

EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events

Stefanos Antaris, Dimitrios Rafailidis, Sarunas Girdzijauskas

In this study, we present a dynamic graph representation learning model on weighted graphs to accurately predict the network capacity of connections between viewers in a live video…

cs.AI2020

VStreamDRLS: Dynamic Graph Representation Learning with Self-Attention for Enterprise Distributed Video Streaming Solutions

Stefanos Antaris, Dimitrios Rafailidis

Live video streaming has become a mainstay as a standard communication solution for several enterprises worldwide. To efficiently stream high-quality live video content to a large…

cs.LG2020

Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation

Stefanos Antaris, Dimitrios Rafailidis

Dynamic graph representation learning strategies are based on different neural architectures to capture the graph evolution over time. However, the underlying neural architectures…

cs.LG2020

On Estimating the Training Cost of Conversational Recommendation Systems

Stefanos Antaris, Dimitrios Rafailidis, Mohammad Aliannejadi

Conversational recommendation systems have recently gain a lot of attention, as users can continuously interact with the system over multiple conversational turns. However, convers…