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437 results on '"Petković, Milan"'

1. PhilHumans: Benchmarking Machine Learning for Personal Health

Author

Liventsev, Vadim, Kumar, Vivek, Susaiyah, Allmin Pradhap Singh, Wu, Zixiu, Rodin, Ivan, Yaar, Asfand, Balloccu, Simone, Beraziuk, Marharyta, Battiato, Sebastiano, Farinella, Giovanni Maria, Härmä, Aki, Helaoui, Rim, Petkovic, Milan, Recupero, Diego Reforgiato, Reiter, Ehud, Riboni, Daniele, and Sterling, Raymond

Subjects
Computer Science - Machine Learning
Abstract

The use of machine learning in Healthcare has the potential to improve patient outcomes as well as broaden the reach and affordability of Healthcare. The history of other application areas indicates that strong benchmarks are essential for the development of intelligent systems. We present Personal Health Interfaces Leveraging HUman-MAchine Natural interactions (PhilHumans), a holistic suite of benchmarks for machine learning across different Healthcare settings - talk therapy, diet coaching, emergency care, intensive care, obstetric sonography - as well as different learning settings, such as action anticipation, timeseries modeling, insight mining, language modeling, computer vision, reinforcement learning and program synthesis

Published
2024

2. Schema-Driven Actionable Insight Generation and Smart Recommendation

Author

Susaiyah, Allmin, Härmä, Aki, and Petković, Milan

Subjects
Computer Science - Computation and Language
Abstract

In natural language generation (NLG), insight mining is seen as a data-to-text task, where data is mined for interesting patterns and verbalised into 'insight' statements. An 'over-generate and rank' paradigm is intuitively used to generate such insights. The multidimensionality and subjectivity of this process make it challenging. This paper introduces a schema-driven method to generate actionable insights from data to drive growth and change. It also introduces a technique to rank the insights to align with user interests based on their feedback. We show preliminary qualitative results of the insights generated using our technique and demonstrate its ability to adapt to feedback.

Published
2023

4. Autoencoders as Tools for Program Synthesis

Author

de Bruin, Sander, Liventsev, Vadim, and Petković, Milan

Subjects
Computer Science - Artificial Intelligence, Computer Science - Programming Languages, I.2.2, I.2.6
Abstract

Recently there have been many advances in research on language modeling of source code. Applications range from code suggestion and completion to code summarization. However, complete program synthesis of industry-grade programming languages remains an open problem. In this work, we introduce and experimentally validate a variational autoencoder model for program synthesis of industry-grade programming languages. This model makes use of the inherent tree structure of code and can be used in conjunction with gradient free optimization techniques like evolutionary methods to generate programs that maximize a given fitness function, for instance, passing a set of test cases. A demonstration is avaliable at https://tree2tree.app, Comment: A dedicted website for demonstrating the principles shown in the paper is available at: https://tree2tree.app/ Source code is available at https://github.com/sander102907/autoencoder_program_synthesis

Published
2021

5. Neurogenetic Programming Framework for Explainable Reinforcement Learning

Author

Liventsev, Vadim, Härmä, Aki, and Petković, Milan

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, I.2.2, I.2.6
Abstract

Automatic programming, the task of generating computer programs compliant with a specification without a human developer, is usually tackled either via genetic programming methods based on mutation and recombination of programs, or via neural language models. We propose a novel method that combines both approaches using a concept of a virtual neuro-genetic programmer: using evolutionary methods as an alternative to gradient descent for neural network training}, or scrum team. We demonstrate its ability to provide performant and explainable solutions for various OpenAI Gym tasks, as well as inject expert knowledge into the otherwise data-driven search for solutions., Comment: Source code is available at https://github.com/vadim0x60/cibi

Published
2021

6. BF++: a language for general-purpose program synthesis

Author

Liventsev, Vadim, Härmä, Aki, and Petković, Milan

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, I.2.2
Abstract

Most state of the art decision systems based on Reinforcement Learning (RL) are data-driven black-box neural models, where it is often difficult to incorporate expert knowledge into the models or let experts review and validate the learned decision mechanisms. Knowledge-insertion and model review are important requirements in many applications involving human health and safety. One way to bridge the gap between data and knowledge driven systems is program synthesis: replacing a neural network that outputs decisions with a symbolic program generated by a neural network or by means of genetic programming. We propose a new programming language, BF++, designed specifically for automatic programming of agents in a Partially Observable Markov Decision Process (POMDP) setting and apply neural program synthesis to solve standard OpenAI Gym benchmarks., Comment: 8+2 pages (paper+references)

Published
2021

7. Artificial Intelligence in Clinical Health Care Applications: Viewpoint

Author

van Hartskamp, Michael, Consoli, Sergio, Verhaegh, Wim, Petković, Milan, and van de Stolpe, Anja

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence
Abstract

The idea of Artificial Intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Currently we are experiencing a renewed interest in AI, fueled by an enormous increase in computing power and an even larger increase in data, in combination with improved AI technologies like deep learning. Healthcare is considered the next domain to be revolutionized by Artificial Intelligence. While AI approaches are excellently suited to develop certain algorithms, for biomedical applications there are specific challenges. We propose recommendations to improve AI projects in the biomedical space and especially clinical healthcare.

Published
2019
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9. Generating High-Resolution 3D Faces Using VQ-VAE-2 with PixelSNAIL Networks

Author

Gallucci, Alessio, Znamenskiy, Dmitry, Pezzotti, Nicola, Petkovic, Milan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Mazzeo, Pier Luigi, editor, Frontoni, Emanuele, editor, Sclaroff, Stan, editor, and Distante, Cosimo, editor

Published
2022
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10. Deep Learning in Information Security

Author

Thaler, Stefan, Menkovski, Vlado, and Petkovic, Milan

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

Machine learning has a long tradition of helping to solve complex information security problems that are difficult to solve manually. Machine learning techniques learn models from data representations to solve a task. These data representations are hand-crafted by domain experts. Deep Learning is a sub-field of machine learning, which uses models that are composed of multiple layers. Consequently, representations that are used to solve a task are learned from the data instead of being manually designed. In this survey, we study the use of DL techniques within the domain of information security. We systematically reviewed 77 papers and presented them from a data-centric perspective. This data-centric perspective reflects one of the most crucial advantages of DL techniques -- domain independence. If DL-methods succeed to solve problems on a data type in one domain, they most likely will also succeed on similar data from another domain. Other advantages of DL methods are unrivaled scalability and efficiency, both regarding the number of examples that can be analyzed as well as with respect of dimensionality of the input data. DL methods generally are capable of achieving high-performance and generalize well. However, information security is a domain with unique requirements and challenges. Based on an analysis of our reviewed papers, we point out shortcomings of DL-methods to those requirements and discuss further research opportunities.

Published
2018

13. Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Author

Gallucci, Alessio, Znamenskiy, Dmitry, Pezzotti, Nicola, Petkovic, Milan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Del Bimbo, Alberto, editor, Cucchiara, Rita, editor, Sclaroff, Stan, editor, Farinella, Giovanni Maria, editor, Mei, Tao, editor, Bertini, Marco, editor, Escalante, Hugo Jair, editor, and Vezzani, Roberto, editor

Published
2021
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15. The European Big Data Value Ecosystem

Author

Curry, Edward, Metzger, Andreas, Zillner, Sonja, Pazzaglia, Jean-Christophe, García Robles, Ana, Hahn, Thomas, Le Bars, Laure, Petkovic, Milan, De Lama, Nuria, Curry, Edward, editor, Metzger, Andreas, editor, Zillner, Sonja, editor, Pazzaglia, Jean-Christophe, editor, and García Robles, Ana, editor

Published
2021
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16. Technical Research Priorities for Big Data

Author

Curry, Edward, Zillner, Sonja, Metzger, Andreas, Berre, Arne J., Auer, Sören, Walshe, Ray, Despenic, Marija, Petkovic, Milan, Roman, Dumitru, Waterfeld, Walter, Seidl, Robert, Hasan, Souleiman, ul Hassan, Umair, Ojo, Adegboyega, Curry, Edward, editor, Metzger, Andreas, editor, Zillner, Sonja, editor, Pazzaglia, Jean-Christophe, editor, and García Robles, Ana, editor

Published
2021
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18. Data Science in Healthcare: Benefits, Challenges and Opportunities

Author

Abedjan, Ziawasch, Boujemaa, Nozha, Campbell, Stuart, Casla, Patricia, Chatterjea, Supriyo, Consoli, Sergio, Costa-Soria, Cristobal, Czech, Paul, Despenic, Marija, Garattini, Chiara, Hamelinck, Dirk, Heinrich, Adrienne, Kraaij, Wessel, Kustra, Jacek, Lojo, Aizea, Sanchez, Marga Martin, Mayer, Miguel A., Melideo, Matteo, Menasalvas, Ernestina, Aarestrup, Frank Moller, Artigot, Elvira Narro, Petković, Milan, Recupero, Diego Reforgiato, Gonzalez, Alejandro Rodriguez, Kerremans, Gisele Roesems, Roller, Roland, Romao, Mario, Ruping, Stefan, Sasaki, Felix, Spek, Wouter, Stojanovic, Nenad, Thoms, Jack, Vasiljevs, Andrejs, Verachtert, Wilfried, Wuyts, Roel, Consoli, Sergio, editor, Reforgiato Recupero, Diego, editor, and Petković, Milan, editor

Published
2019
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20. Enforcing Access Control in Virtual Organizations Using Hierarchical Attribute-Based Encryption

Author

Asim, Muhammad, Ignatenko, Tanya, Petkovic, Milan, Trivellato, Daniel, and Zannone, Nicola

Subjects
Computer Science - Cryptography and Security
Abstract

Virtual organizations are dynamic, inter-organizational collaborations that involve systems and services belonging to different security domains. Several solutions have been proposed to guarantee the enforcement of the access control policies protecting the information exchanged in a distributed system, but none of them addresses the dynamicity characterizing virtual organizations. In this paper we propose a dynamic hierarchical attribute-based encryption (D-HABE) scheme that allows the institutions in a virtual organization to encrypt information according to an attribute-based policy in such a way that only users with the appropriate attributes can decrypt it. In addition, we introduce a key management scheme that determines which user is entitled to receive which attribute key from which domain authority.

Published
2012

21. Deep Metric Learning for Sequential Data Using Approximate Information

Author

Thaler, Stefan, Menkovski, Vlado, Petkovic, Milan, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, and Perner, Petra, editor

Published
2018
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23. Unsupervised Signature Extraction from Forensic Logs

Author

Thaler, Stefan, Menkovski, Vlado, Petkovic, Milan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Altun, Yasemin, editor, Das, Kamalika, editor, Mielikäinen, Taneli, editor, Malerba, Donato, editor, Stefanowski, Jerzy, editor, Read, Jesse, editor, Žitnik, Marinka, editor, Ceci, Michelangelo, editor, and Džeroski, Sašo, editor

Published
2017
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25. Security, Privacy and Trust: From Innovation Blocker to Innovation Enabler

Author

Jonker, Willem, Petković, Milan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Jonker, Willem, editor, and Petković, Milan, editor

Published
2014
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26. Towards Creating Believable Decoy Project Folders for Detecting Data Theft

Author

Thaler, Stefan, den Hartog, Jerry, Petkovic, Milan, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ranise, Silvio, editor, and Swarup, Vipin, editor

Published
2016
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28. Towards Trustworthy Health Platform Cloud

Author

Deng, Mina, Nalin, Marco, Petković, Milan, Baroni, Ilaria, Marco, Abitabile, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Jonker, Willem, editor, and Petković, Milan, editor

Published
2012
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29. Purpose Control: Did You Process the Data for the Intended Purpose?

Author

Petković, Milan, Prandi, Davide, Zannone, Nicola, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Jonker, Willem, editor, and Petković, Milan, editor

Published
2011
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30. DRM for Protecting Personal Content

Author

Li, Hong, Petković, Milan, Carey, M. J., editor, Ceri, S., editor, Bernstein, P., editor, Dayal, U., editor, Faloutsos, C., editor, Freytag, J. C., editor, Gardarin, G., editor, Jonker, W., editor, Krishnamurthy, V., editor, Neimat, M. -A., editor, Valduriez, P., editor, Weikum, G., editor, Whang, K. -Y., editor, Widom, J., editor, Petković, Milan, editor, and Jonker, Willem, editor

Published
2007
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31. Enhancing Privacy for Digital Rights Management

Author

Petković, Milan, Conrado, Claudine, Schrijen, Geert-Jan, Jonker, Willem, Carey, M. J., editor, Ceri, S., editor, Bernstein, P., editor, Dayal, U., editor, Faloutsos, C., editor, Freytag, J. C., editor, Gardarin, G., editor, Jonker, W., editor, Krishnamurthy, V., editor, Neimat, M. -A., editor, Valduriez, P., editor, Weikum, G., editor, Whang, K. -Y., editor, Widom, J., editor, Petković, Milan, editor, and Jonker, Willem, editor

Published
2007
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32. Privacy and Security Issues in a Digital World

Author

Petković, Milan, Jonker, Willem, Carey, M. J., editor, Ceri, S., editor, Bernstein, P., editor, Dayal, U., editor, Faloutsos, C., editor, Freytag, J. C., editor, Gardarin, G., editor, Jonker, W., editor, Krishnamurthy, V., editor, Neimat, M. -A., editor, Valduriez, P., editor, Weikum, G., editor, Whang, K. -Y., editor, Widom, J., editor, Petković, Milan, editor, and Jonker, Willem, editor

Published
2007
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41. Privacy-Preserving Digital Rights Management

Author

Conrado, Claudine, Petković, Milan, Jonker, Willem, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Jonker, Willem, editor, and Petković, Milan, editor

Published
2004
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42. Data Leakage Quantification

Author

Vavilis, Sokratis, Petković, Milan, Zannone, Nicola, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Atluri, Vijay, editor, and Pernul, Günther, editor

Published
2014
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43. Hunting the Unknown : White-Box Database Leakage Detection

Author

Costante, Elisa, den Hartog, Jerry, Petković, Milan, Etalle, Sandro, Pechenizkiy, Mykola, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Atluri, Vijay, editor, and Pernul, Günther, editor

Published
2014
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44. AU2EU: Privacy-Preserving Matching of DNA Sequences

Author

Ignatenko, Tanya, Petković, Milan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Naccache, David, editor, and Sauveron, Damien, editor

Published
2014
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45. What Websites Know About You : Privacy Policy Analysis Using Information Extraction

Author

Costante, Elisa, den Hartog, Jerry, Petković, Milan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Di Pietro, Roberto, editor, Herranz, Javier, editor, Damiani, Ernesto, editor, and State, Radu, editor

Published
2013
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47. Impact of ICT on Home Healthcare

Author

Vavilis, Sokratis, Petković, Milan, Zannone, Nicola, Hercheui, Magda David, editor, Whitehouse, Diane, editor, McIver, William, Jr., editor, and Phahlamohlaka, Jackie, editor

Published
2012
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48. Measuring Privacy Compliance Using Fitness Metrics

Author

Banescu, Sebastian, Petković, Milan, Zannone, Nicola, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Barros, Alistair, editor, Gal, Avigdor, editor, and Kindler, Ekkart, editor

Published
2012
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50. Melatonin reduces lipopolysaccharide-induced kidney damage in rats

Author

Sokolović, Danka, Lazarević, Milan, Milić, Dragan, Stanojković, Zoran, Petković, Milan N., Stojanović, Nikola M., and Sokolović, Dušan T.

Subjects
kidney, lipopolysaccharide, creatinine, melatonin, urea
Abstract

Lipopolysaccharide (LPS) is a constituent of Gram-negative bacterial cell walls, thus LPS injection has been widely used as a model of experimental acute kidney injury associated with sepsis. LPS-induced sepsis is caused by excessive secretion of proinflammatory mediators and reactive oxygen species (ROS). The neurohormone melatonin, which is mainly secreted by the pineal gland, regulates the circadian rhythm, has an anti-inflammatory and immunoregulatory role. Melatonin and its metabolites have been shown to scavenge various free radicals and reactive oxygen intermediates. The aim of this study was to evaluate the effect of melatonin in preventing endotoxemia-induced kidney damage caused by LPS, by analysing the concentration of urea and creatinine in the blood serum of rats. Twenty-eight Wistar albino rats were randomly divided into four groups (n = 7 per group) as follows: 1) Control group, 2) MLT group (50 mg/kg, per os), 3) LPS group (10 mg/kg, i.p.) and 4) LPS + MLT group (10 mg/kg + 50 mg/kg). Serum levels of creatinine and urea were significantly higher (p

Published
2023

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