17 citations · 29 across the 6 of their papers we have counts for
9 papers
Maximizing Influence with Graph Neural Networks
George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis +1
Finding the seed set that maximizes the influence spread over a network is a well-known NP-hard problem. Though a greedy algorithm can provide near-optimal solutions, the subproble…
Predicting conversions in display advertising based on URL embeddings
Yang Qiu, Nikolaos Tziortziotis, Martial Hue +1
Online display advertising is growing rapidly in recent years thanks to the automation of the ad buying process. Real-time bidding (RTB) allows the automated trading of ad impressi…
Randomised Bayesian Least-Squares Policy Iteration
Nikolaos Tziortziotis, Christos Dimitrakakis, Michalis Vazirgiannis
We introduce Bayesian least-squares policy iteration (BLSPI), an off-policy, model-free, policy iteration algorithm that uses the Bayesian least-squares temporal-difference (BLSTD)…
Orthogonal Matching Pursuit for Text Classification
Konstantinos Skianis, Nikolaos Tziortziotis, Michalis Vazirgiannis
In text classification, the problem of overfitting arises due to the high dimensionality, making regularization essential. Although classic regularizers provide sparsity, they fail…
Adaptive Submodular Influence Maximization with Myopic Feedback
Guillaume Salha, Nikolaos Tziortziotis, Michalis Vazirgiannis
This paper examines the problem of adaptive influence maximization in social networks. As adaptive decision making is a time-critical task, a realistic feedback model has been cons…
A k-core Decomposition Framework for Graph Clustering
Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis +4
Graph clustering or community detection constitutes an important task for investigating the internal structure of graphs, with a plethora of applications in several domains. Tradit…
A Bayesian Ensemble Regression Framework on the Angry Birds Game
Nikolaos Tziortziotis, Georgios Papagiannis, Konstantinos Blekas
An ensemble inference mechanism is proposed on the Angry Birds domain. It is based on an efficient tree structure for encoding and representing game screenshots, where it exploits…
Cover Tree Bayesian Reinforcement Learning
Nikolaos Tziortziotis, Christos Dimitrakakis, Konstantinos Blekas
This paper proposes an online tree-based Bayesian approach for reinforcement learning. For inference, we employ a generalised context tree model. This defines a distribution on mul…
ABC Reinforcement Learning
Christos Dimitrakakis, Nikolaos Tziortziotis
This paper introduces a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The main advantage is that we…