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Alexandros Karatzoglou

Alexandros Karatzoglou

D-Index & Metrics

Computer Science

D-Index
41
Citations
14089
World Ranking
8598
National Ranking
3684

Overview

Alexandros Karatzoglou is affiliated with Google in the United States and primarily conducts research in Computer Science. Their work spans multiple subfields including Artificial Intelligence, Information Systems, Management Science and Operations Research, Electrical and Electronic Engineering, and Computer Vision and Pattern Recognition.

The main topics Alexandros Karatzoglou focuses on include Recommender Systems and Techniques, Advanced Bandit Algorithms Research, Reinforcement Learning in Robotics, Smart Grid Energy Management, Advanced Graph Neural Networks, Topic Modeling, and Domain Adaptation and Few-Shot Learning.

Recent publications by Alexandros Karatzoglou cover several contributions to recommender systems and reinforcement learning. Notable papers include:

  • "Supervised Advantage Actor-Critic for Recommender Systems" (2022), Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • "Rethinking Reinforcement Learning for Recommendation" (2022), Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "Choosing the Best of Both Worlds" (2022), Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • "Self-Supervised Reinforcement Learning for Recommender Systems" (2020), arXiv (Cornell University)
  • "One Person, One Model, One World: Learning Continual User Representation without Forgetting" (2020), arXiv (Cornell University)

They have collaborated frequently with several coauthors, including Xin Xin, Ioannis Arapakis, Joemon M. Jose, Fajie Yuan, and Dušan Stamenković.

Alexandros Karatzoglou's works are published in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Access

Best Publications

  • kernlab - An S4 Package for Kernel Methods in R

    Alexandros Karatzoglou;Alexandros Smola;Kurt Hornik;Achim Zeileis

  • Session-based Recommendations with Recurrent Neural Networks

    Balázs Hidasi;Alexandros Karatzoglou;Linas Baltrunas;Domonkos Tikk

  • Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

    Massimo Quadrana;Alexandros Karatzoglou;Balázs Hidasi;Paolo Cremonesi

  • Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering

    Alexandros Karatzoglou;Xavier Amatriain;Linas Baltrunas;Nuria Oliver

  • Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

    Balázs Hidasi;Alexandros Karatzoglou

  • Support Vector Machines in R

    Alexandros Karatzoglou;David Meyer;Kurt Hornik

  • Recurrent neural networks

    Stephen Grossberg

  • Overcoming catastrophic forgetting with hard attention to the task

    Joan Serrà;Dídac Surís;Marius Miron;Alexandros Karatzoglou

  • A Simple Convolutional Generative Network for Next Item Recommendation

    Fajie Yuan;Alexandros Karatzoglou;Ioannis Arapakis;Joemon M. Jose

  • Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations

    Balázs Hidasi;Massimo Quadrana;Alexandros Karatzoglou;Domonkos Tikk

  • CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering

    Yue Shi;Alexandros Karatzoglou;Linas Baltrunas;Martha Larson

  • Collaborative Filtering Bandits

    Shuai Li;Alexandros Karatzoglou;Claudio Gentile

  • TFMAP: optimizing MAP for top-n context-aware recommendation

    Yue Shi;Alexandros Karatzoglou;Linas Baltrunas;Martha Larson

  • Self-Supervised Reinforcement Learning for Recommender Systems

    Xin Xin;Alexandros Karatzoglou;Ioannis Arapakis;Joemon M. Jose

  • Coverage, redundancy and size-awareness in genre diversity for recommender systems

    Saúl Vargas;Linas Baltrunas;Alexandros Karatzoglou;Pablo Castells

  • Improving maximum margin matrix factorization

    Markus Weimer;Alexandros Karatzoglou;Alex Smola

  • Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation

    Fajie Yuan;Xiangnan He;Alexandros Karatzoglou;Liguang Zhang

  • Learning to rank for recommender systems

    Alexandros Karatzoglou;Linas Baltrunas;Yue Shi

  • Proceedings of the 1st Workshop on Deep Learning for Recommender Systems

    Alexandros Karatzoglou;Balázs Hidasi;Domonkos Tikk;Oren Sar-Shalom

  • Climbing the app wall: enabling mobile app discovery through context-aware recommendations

    Alexandros Karatzoglou;Linas Baltrunas;Karen Church;Matthias Böhmer

  • RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising

    David Rohde;Stephen Bonner;Travis Dunlop;Flavian Vasile

  • On Context-Dependent Clustering of Bandits

    Claudio Gentile;Shuai Li;Purushottam Kar;Alexandros Karatzoglou

Frequent Co-Authors

Martha Larson
Martha Larson Radboud University
Domonkos Tikk
Domonkos Tikk Gravity Research & Development Zrt.
Nuria Oliver
Nuria Oliver European Laboratory for Learning and Intelligent Systems
Alan Hanjalic
Alan Hanjalic Delft University of Technology
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Joemon M. Jose
Joemon M. Jose University of Glasgow
Claudio Gentile
Claudio Gentile Google (United States)
Kurt Hornik
Kurt Hornik Vienna University of Economics and Business
Paolo Cremonesi
Paolo Cremonesi Polytechnic University of Milan
Xiangnan He
Xiangnan He University of Science and Technology of China

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