Michal Valko : Research
My Google Scholar profile and HAL profile.

2017

  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Efficient second-order online kernel learning with adaptive embedding, in Neural Information Processing Systems (NIPS 2017) bibtex abstract abstract talk
  • Zheng Wen, Branislav Kveton , Michal Valko, Sharan Vaswani: Online influence maximization under independent cascade model with semi-bandit feedback, in Neural Information Processing Systems (NIPS 2017) bibtex abstract abstract
  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Second-order kernel online convex optimization with adaptive sketching, in International Conference on Machine Learning (ICML 2017) bibtex abstract abstract talk poster
  • Guillaume Gautier, Rémi Bardenet, Michal Valko: Zonotope hit-and-run for efficient sampling from projection DPPs, in International Conference on Machine Learning (ICML 2017) bibtex abstract abstract talk poster
  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Distributed sequential sampling for kernel matrix approximation, in International Conference on Artificial Intelligence and Statistics (AISTATS 2017) and (ICML 2017 - LL) bibtex abstract abstract talk code poster
  • Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yu-En Liu: Trading off rewards and errors in multi-armed bandits, in International Conference on Artificial Intelligence and Statistics (AISTATS 2017) bibtex abstract abstract poster
  • Tomáš Kocák, Michal Valko, Rémi Munos, Branislav Kveton, Shipra Agrawal: Spectral Bandits, accepted for publication to Journal of Machine Learning Research (JMLR 2017)
  • Branislav Kveton, Zheng Wen, Azin Ashkan, Michal Valko: Learning to Act Greedily: Polymatroid Semi-Bandits, accepted for publication to Journal of Machine Learning Research (JMLR 2017) bibtex abstract abstract arXiv preprint

2016

  • Michal Valko: Bandits on graphs and structures, habilitation thesis, École normale supérieure de Cachan (ENS Cachan 2016) bibtex abstract abstract
  • Jean-Bastien Grill, Michal Valko, Rémi Munos: Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning, in Neural Information Processing Systems (NIPS 2016) bibtex abstract abstract talk poster [full oral presentation - 1.8% acceptance rate]
  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Pack only the essentials: Adaptive dictionary learning for kernel ridge regression, in Adaptive and Scalable Nonparametric Methods in Machine Learning at Neural Information Processing Systems (NIPS 2016 - ASNMML) bibtex abstract abstract poster
  • Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yu-En Liu: Rewards and Errors in Multi-armed Bandit for Interactive Education, in Challenges in Machine Learning: Gaming and Education workshop at Neural Information Processing Systems (NIPS 2016 - CIML) bibtex abstract abstract poster
  • Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard: Pliable rejection sampling, in International Conference on Machine Learning (ICML 2016) bibtex abstract abstract talk poster
  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Analysis of Nyström method with sequential ridge leverage scores, in Uncertainty in Artificial Intelligence (UAI 2016) bibtex abstract abstract poster spotlight
  • Tomáš Kocák, Gergely Neu, Michal Valko: Online learning with Erdős-Rényi side-observation graphs, in Uncertainty in Artificial Intelligence (UAI 2016) bibtex abstract abstract poster spotlight
  • Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko: Bayesian policy gradient and actor-critic algorithms, Journal of Machine Learning Research (JMLR 2016) bibtex abstract abstract code
  • Tomáš Kocák, Gergely Neu, Michal Valko: Online learning with noisy side observations, in International Conference on Artificial Intelligence and Statistics (AISTATS 2016) bibtex abstract abstract talk poster [full oral presentation - 6% acceptance rate]
  • Alexandra Carpentier, Michal Valko: Revealing graph bandits for maximizing local influence, in International Conference on Artificial Intelligence and Statistics (AISTATS 2016) bibtex abstract abstract poster

2015

  • Jean-Bastien Grill, Michal Valko, Rémi Munos: Black-box optimization of noisy functions with unknown smoothness, in Neural Information Processing Systems (NIPS 2015) bibtex abstract abstract code, code in R poster
  • Alexandra Carpentier, Michal Valko: Simple regret for infinitely many armed bandits, in International Conference on Machine Learning (ICML 2015) bibtex abstract abstract talk poster arXiv
  • Manjesh Hanawal, Venkatesh Saligrama, Michal Valko, Rémi Munos: Cheap Bandits, in International Conference on Machine Learning (ICML 2015) bibtex abstract abstract talk poster
  • Daniele Calandriello, Alessandro Lazaric, Michal Valko: Large-scale semi-supervised learning with online spectral graph sparsification, in Resource-Efficient Machine Learning workshop at International Conference on Machine Learning (ICML 2015 - REML) bibtex abstract abstract poster
  • Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh: Maximum Entropy Semi-Supervised Inverse Reinforcement Learning, in International Joint Conferences on Artificial Intelligence (IJCAI 2015) bibtex abstract abstract talk poster

2014

  • Tomáš Kocák, Gergely Neu, Michal Valko, Rémi Munos: Efficient Learning by Implicit Exploration in Bandit Problems with Side Observations, in Neural Information Processing Systems (NIPS 2014) bibtex abstract abstracttalk poster
  • Alexandra Carpentier, Michal Valko: Extreme Bandits, in Neural Information Processing Systems (NIPS 2014) bibtex abstract abstractposter
  • Gergely Neu, Michal Valko: Online Combinatorial Optimization with Stochastic Decision Sets and Adversarial Losses, in Neural Information Processing Systems (NIPS 2014) bibtex abstract abstracttalk poster
  • Michal Valko, Rémi Munos, Branislav Kveton, Tomáš Kocák: Spectral Bandits for Smooth Graph Functions, in International Conference on Machine Learning (ICML 2014) bibtex abstract abstractslides poster
  • Tomáš Kocák, Michal Valko, Rémi Munos, Shipra Agrawal: Spectral Thompson Sampling, in AAAI Conference on Artificial Intelligence (AAAI 2014) bibtex abstract abstractslides poster
  • Philippe Preux, Rémi Munos, Michal Valko: Bandits attack function optimization, in IEEE Congress on Evolutionary Computation (CEC 2014) bibtex abstract abstract
  • Julien Audiffren, Michal Valko, Alessandro Lazaric, Mohammad Ghavamzadeh: MESSI: Maximum Entropy Semi-Supervised Inverse Reinforcement Learning, in NIPS Workshop on Novel Trends and Applications in Reinforcement Learning (NIPS 2014 - TCRL) bibtex abstract abstract
  • Tomáš Kocák, Michal Valko, Rémi Munos, Branislav Kveton, Shipra Agrawal: Spectral Bandits for Smooth Graph Functions with Applications in Recommender Systems, in AAAI Workshop on Sequential Decision-Making with Big Data (AAAI 2014 - SDMBD) bibtex abstract abstract

2013

  • Michal Valko, Alexandra Carpentier, Rémi Munos: Stochastic Simultaneous Optimistic Optimization, in International Conference on Machine Learning (ICML 2013) bibtex abstract abstract demo code, code in R slides poster talk
  • Michal Valko, Nathan Korda, Rémi Munos, Ilias Flaounas, Nello Cristianini: Finite-Time Analysis of Kernelised Contextual Bandits, in Uncertainty in Artificial Intelligence (UAI 2013) and (JFPDA 2013). bibtex abstract abstract poster spotlight code
  • Branislav Kveton, Michal Valko: Learning from a Single Labeled Face and a Stream of Unlabeled Data, in IEEE International Conference on Automatic Face and Gesture Recognition (FG 2013) [spotlight] bibtex abstract abstract
  • Milos Hauskrecht, Iyad Batal, Michal Valko, Shyam Visweswaran, Gregory F. Cooper, Gilles Clermont: Outlier detection for patient monitoring and alerting, in Journal of Biomedical Informatics (JBI 2013) bibtex abstract abstract

2012

  • Michal Valko, Mohammad Ghavamzadeh, Alessandro Lazaric: Semi-supervised apprenticeship learning, in Journal of Machine Learning Research Workshop and Conference Proceedings: European Workshop on Reinforcement Learning (EWRL 2012) bibtex abstract abstracttalk poster

2011

  • Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht: Conditional Anomaly Detection with Soft Harmonic Functions, in International Conference on Data Mining (ICDM 2011) bibtex abstract abstract
  • Thomas C. Hart, Patricia M. Corby, Milos Hauskrecht, Ok Hee Ryu, Richard Pelikan, Michal Valko, Maria B. Oliveira, Gerald T. Hoehn, and Walter A. Bretz: Identification of Microbial and Proteomic Biomarkers in Early Childhood Caries in International Journal of Dentistry (IJD 2011) bibtex abstract abstract
  • Michal Valko: Adaptive Graph-Based Algorithms for Conditional Anomaly Detection and Semi-Supervised Learning, PhD thesis, University of Pittsburgh (PITT 2011) bibtex abstract abstract
  • Michal Valko, Hamed Valizadegan, Branislav Kveton, Gregory F. Cooper, Milos Hauskrecht: Conditional Anomaly Detection Using Soft Harmonic Functions: An Application to Clinical Alerting, Workshop on Machine Learning for Global Challenges in International Conference on Machine Learning (ICML 2011 - Global) bibtex abstract abstract poster spotlight

2010

  • Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting: Online Semi-Supervised Learning on Quantized Graphs in Uncertainty in Artificial Intelligence (UAI 2010) bibtex abstract abstract Video: Adaptation, Video: OfficeSpace, spotlight poster
  • Branislav Kveton, Michal Valko, Ali Rahimi, Ling Huang: Semi-Supervised Learning with Max-Margin Graph Cuts in International Conference on Artificial Intelligence and Statistics (AISTATS 2010) bibtex abstract abstract
  • Milos Hauskrecht, Michal Valko, Shyam Visweswaram, Iyad Batal, Gilles Clermont, Gregory Cooper: Conditional Outlier Detection for Clinical Alerting in Annual American Medical Informatics Association conference (AMIA 2010) bibtex abstract abstract [Homer Warner Best Paper Award]
  • Branislav Kveton, Michal Valko, Matthai Phillipose, Ling Huang: Online Semi-Supervised Perception: Real-Time Learning without Explicit Feedback in IEEE Online Learning for Computer Vision Workshop in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010 - OLCV) [best paper Google Award] bibtex abstract abstract
  • Michal Valko, Milos Hauskrecht: Feature importance analysis for patient management decisions in International Congress on Medical Informatics (MEDINFO 2010) bibtex abstract abstract

2008

  • Michal Valko, Gregory Cooper, Amy Seybert, Shyam Visweswaran, Melissa Saul, Milos Hauskrecht: Conditional anomaly detection methods for patient-management alert systems, Workshop on Machine Learning in Health Care Applications in International Conference on Machine Learning (ICML-2008 - MLHealth) bibtex abstract abstract talk
  • Michal Valko, Milos Hauskrecht: Distance metric learning for conditional anomaly detection, International Florida AI Research Society Conference (FLAIRS 2008) bibtex abstract abstract
  • Michal Valko, Richard Pelikan, Milos Hauskrecht: Learning predictive models for combinations of heterogeneous proteomic data sources, AMIA Summit on Translational Bioinformatics (STB 2008) [outstanding paper award] bibtex abstract abstracttalk

2007

  • Milos Hauskrecht, Michal Valko, Branislav Kveton, Shyam Visweswaram, Gregory Cooper: Evidence-based Anomaly Detection in Clinical Domains in Annual American Medical Informatics Association conference (AMIA 2007). [nominated for the best paper award] bibtex abstract abstract

2006

  • Wendy W. Chapman, John N. Dowling, Gregory F. Cooper, Milos Hauskrecht and Michal Valko: A Comparison of Chief Complaints and Emergency Department Reports for Identifying Patients with Acute Lower Respiratory Syndrome in Proceedings of the National Syndromic Surveillance Conference (ISDS 2006) bibtex abstract abstract
  • Miloš Hauskrecht, Richard Pelikan, Michal Valko, James Lyons-Weiler: Feature Selection and Dimensionality Reduction in Genomics and Proteomics. Fundamentals of Data Mining in Genomics and Proteomics, eds. Berrar, Dubitzky, Granzow. Springer (2006) bibtex abstract abstract

2005

  • Michal Valko, Nuno C. Marques, Marco Castelani: Evolutionary Feature Selection for Spiking Neural Network Pattern Classifiers in Proceedings of Portuguese Conference on Artificial Intelligence (EPIA 2005), eds. Bento et al., IEEE, pages 24-32. bibtex abstract abstract
  • Michal Valko Evolving Neural Networks for Statistical Decision Theory, Comenius University, Bratislava, 2005 (master thesis) (2005) Advisor: Radoslav Harman thesis@sk bibtex abstract abstract talk

Presentations

  • Michal Valko: Graph-Based Anomaly Detection with Soft Harmonic Functions: Presented at CS Department Research Competition (Research 2011) [#1st place] talk also at (Grad Expo 2011) and (CS DAY 2011) poster
  • Branislav Kveton, Michal Valko, Matthai Philiposse: Real-Time Adaptive Face Recognition, Presented at 23rd Neural Information Processing Systems conference (NIPS 2009), Video: Adaptation, Video: OfficeSpace, poster #1, poster #2
  • Michal Valko:, Branislav Kveton, Matthai Philiposse: Robust Face Recognition Using Online Learning, Presented at 9th University of Pittsburgh Science conference (SCIENCE 2009) Live Demonstration (Grad Expo 2010) talk and (CS Day 2010) poster
  • Michal Valko: Conditional anomaly detection with adaptive similarity metric: Presented at CS Department Research Competition (Research 2008) [#1st place] talk
  • Michal Valko, Milos Hauskrecht, G. Cooper, S. Visweswaran, M. Saul, A. Seybert, J. Harrison, A. Post: Conditional Anomaly Detection, Presented at (CS Day 2008) [#1st by people, #2nd by faculty] also at University of Pittsburgh, Arts & Sciences (Grad Expo 2008) poster

References

12-Nov-2015