599 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National and Kapodistrian University of AthensGR24 papers
- National Technical University of AthensGR11 papers
- Athena Research and Innovation Center In Information Communication & Knowledge TechnologiesGR9 papers
- Athens State UniversityUS7 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Centrum Wiskunde & InformaticaNL7 papers
- Delft University of TechnologyNL7 papers
- École PolytechniqueFR7 papers
- University College LondonGB7 papers
- University of OxfordGB7 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR6 papers
- University of AmsterdamNL6 papers
21 papers · 1 filter
Extracting Linguistic Resources from the Web for Concept-to-Text Generation
Gerasimos Lampouras, Ion Androutsopoulos
Many concept-to-text generation systems require domain-specific linguistic resources to produce high quality texts, but manually constructing these resources can be tedious and cos…
Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules
Michalis K. Titsias, Sotirios Nikoloutsopoulos
We propose a probabilistic framework to directly insert prior knowledge in reinforcement learning (RL) algorithms by defining the behaviour policy as a Bayesian posterior distribut…
Deep Relevance Ranking Using Enhanced Document-Query Interactions
Ryan McDonald, Georgios-Ioannis Brokos, Ion Androutsopoulos
We explore several new models for document relevance ranking, building upon the Deep Relevance Matching Model (DRMM) of Guo et al. (2016). Unlike DRMM, which uses context-insensiti…
Measuring Market Performance with Stochastic Demand: Price of Anarchy and Price of Uncertainty
Costis Melolidakis, Stefanos Leonardos, Constandina Koki
Globally operating suppliers face the rising challenge of wholesale pricing under scarce data about retail demand, in contrast to better informed, locally operating retailers. At t…
A Simple Network of Nodes Moving on the Circle
Dimitris Cheliotis, Ioannis Kontoyiannis, Michail Loulakis +1
Two simple Markov processes are examined, one in discrete and one in continuous time, arising from idealized versions of a transmission protocol for mobile, delay-tolerant networks…
Unbiased Implicit Variational Inference
Michalis K. Titsias, Francisco J. R. Ruiz
We develop unbiased implicit variational inference (UIVI), a method that expands the applicability of variational inference by defining an expressive variational family. UIVI consi…
Astraea: A Decentralized Blockchain Oracle
John Adler, Ryan Berryhill, Andreas Veneris +3
The public blockchain was originally conceived to process monetary transactions in a peer-to-peer network while preventing double-spending. It has since been extended to numerous o…
Probability Based Independence Sampler for Bayesian Quantitative Learning in Graphical Log-Linear Marginal Models
Ioannis Ntzoufras, Claudia Tarantola, Monia Lupparelli
Bayesian methods for graphical log-linear marginal models have not been developed in the same extent as traditional frequentist approaches. In this work, we introduce a novel Bayes…
GraKeL: A Graph Kernel Library in Python
Giannis Siglidis, Giannis Nikolentzos, Stratis Limnios +3
The problem of accurately measuring the similarity between graphs is at the core of many applications in a variety of disciplines. Graph kernels have recently emerged as a promisin…
Bayesian forecasting of mortality rates using latent Gaussian models
Angelos Alexopoulos, Petros Dellaportas, Jonathan J. Forster
We provide forecasts for mortality rates by using two different approaches. First we employ dynamic non-linear logistic models based on Heligman-Pollard formula. Second, we assume…
Pairwise likelihood estimation of latent autoregressive count models
Xanthi Pedeli, Cristiano Varin
Latent autoregressive models are useful time series models for the analysis of infectious disease data. Evaluation of the likelihood function of latent autoregressive models is int…
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
Guokan Shang, Wensi Ding, Zekun Zhang +4
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations. Our work combines the stren…
Subwavelength Interferometric Control of Absorption in Three-port Acoustic Network
O. Richoux, V. Achilleos, G. Theocharis +1
Utilizing the effect of losses, we show that symmetric 3-port devices exhibit coherent perfect absorption of waves and we provide the corresponding conditions on the reflection and…
Dietcoin: shortcutting the Bitcoin verification process for your smartphone
Davide Frey, Marc X. Makkes, Pierre-Louis Roman +2
Blockchains have a storage scalability issue. Their size is not bounded and they grow indefinitely as time passes. As of August 2017, the Bitcoin blockchain is about 120 GiB big wh…
Code Review Comments: Language Matters
Vasiliki Efstathiou, Diomidis Spinellis
Recent research provides evidence that effective communication in collaborative software development has significant impact on the software development lifecycle. Although related…
Comparative Statics via Stochastic Orderings in a Two-Echelon Market with Upstream Demand Uncertainty
Constandina Koki, Stefanos Leonardos, Costis Melolidakis
We revisit the classic Cournot model and extend it to a two-echelon supply chain with an upstream supplier who operates under demand uncertainty and multiple downstream retailers w…
ICN enabling CoAP Extensions for IP based IoT devices
Nikos Fotiou, George Xylomenos, George C. Polyzos +4
The Constrained Application Protocol (CoAP) and its extensions, such as observe and group communication, offer the potential for developing novel IoT applications. However, a full-…
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng +1
Categorical distributions are ubiquitous in machine learning, e.g., in classification, language models, and recommendation systems. However, when the number of possible outcomes is…
Low-Rank Methods in Event Detection and Subsampled Point-to-Subspace Proximity Tests
Jakub Marecek, Stathis Maroulis, Vana Kalogeraki +1
Monitoring of streamed data to detect abnormal behaviour (variously known as event detection, anomaly detection, change detection, or outlier detection) underlies many applications…
Forecasting under model uncertainty:Non-homogeneous hidden Markov models with Polya-Gamma data augmentation
Constandina Koki, Loukia Meligkotsidou, Ioannis Vrontos
We consider two-state Non-Homogeneous Hidden Markov Models (NHHMMs) for forecasting univariate time series. Given a set of predictors, the time series are modeled via predictive re…
Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning
Kostas Florios, Ioannis Kontogiannis, Sung-Hong Park +4
We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (S…