2020
- Xuedong Shang, Rianne de Heide, Emilie Kaufmann, Pierre Ménard, Michal Valko:
Fixed-confidence guarantees for Bayesian best-arm identification , in International Conference on Artificial Intelligence and Statistics (AISTATS 2020) arXiv preprint - Côme Fiegel, Victor Gabillon, Michal Valko:
Adaptive multi-fidelity optimization with fast learning rates in International Conference on Artificial Intelligence and Statistics (AISTATS 2020) - Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou Ammar:
Derivative-free & order-robust optimisation in International Conference on Artificial Intelligence and Statistics (AISTATS 2020) - Julien Seznec, Pierre Ménard, Alessandro Lazaric, Michal Valko:
A single algorithm for both restless and rested rotting bandits , in International Conference on Artificial Intelligence and Statistics (AISTATS 2020) talk - Tomáš Kocák, Rémi Munos, Branislav Kveton, Shipra Agrawal, Michal Valko:
Spectral Bandits , accepted for publication to Journal of Machine Learning Research (JMLR 2020) - 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 2020) bibtex abstract arXiv preprint
2019
- Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco:
Scaling parallel Gaussian process optimization with adaptive batching and resparsification , in Optimization for Machine Learning (OPT 2019) bibtex - Jean-Bastien Grill*, Omar Darwiche Domingues*, Pierre Ménard, Rémi Munos, Michal Valko:
Planning in entropy-regularized Markov decision processes and games, in Neural Information Processing Systems (NeurIPS 2019) bibtex - Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos:
Multiagent evaluation under incomplete information, in Neural Information Processing Systems (NeurIPS 2019) bibtex - Michał Dereziński*, Daniele Calandriello*, Michal Valko: Exact sampling of determinantal point processes with sublinear time preprocessing, in Neural Information Processing Systems (NeurIPS 2019) and (ICML 2019 - NEGDEP) bibtex abstract talk video
- Guillaume Gautier, Rémi Bardenet, Michal Valko:
On two ways to use determinantal point processes for Monte Carlo integration , in Neural Information Processing Systems (NeurIPS 2019) and (ICML 2019 - NEGDEP) bibtex video - Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco: Gaussian process optimization with adaptive sketching: Scalable and no regret, in Conference on Learning Theory (COLT 2019) and (ICML 2019 - NEGDEP) and (SWSL 2019) bibtex abstract video talk poster
- Peter Bartlett, Victor Gabillon, Jennifer Healey, Michal Valko: Scale-free adaptive planning for deterministic dynamics & discounted rewards in International Conference on Machine Learning (ICML 2019) bibtex abstract video talk poster
- Pierre Perrault, Vianney Perchet, Michal Valko: Exploiting structure of uncertainty for efficient matroid semi-bandits, in International Conference on Machine Learning (ICML 2019) bibtex abstract video talk poster
- Xuedong Shang, Emilie Kaufmann, Michal Valko: A simple dynamic bandit-based algorithm for hyper-parameter tuning, in Workshop on Automated Machine Learning at International Conference on Machine Learning (ICML 2019 - AutoML) bibtex abstract poster code
- Guillaume Gautier, Rémi Bardenet, Michal Valko: DPPy: Sampling determinantal point processes with Python, Journal of Machine Learning Research (JMLR 2019) bibtex abstract arXiv preprint
- Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko: Rotting bandits are not harder than stochastic ones, in International Conference on Artificial Intelligence and Statistics (AISTATS 2019) bibtex abstract talk poster [full oral presentation - 2.5% acceptance rate]
- Andrea Locatelli, Alexandra Carpentier, Michal Valko:
Active multiple matrix completion with adaptive confidence sets , in International Conference on Artificial Intelligence and Statistics (AISTATS 2019) bibtex abstract talk poster - Pierre Perrault, Vianney Perchet, Michal Valko: Finding the bandit in a graph: Sequential search-and-stop, in International Conference on Artificial Intelligence and Statistics (AISTATS 2019) bibtex abstract poster
- Peter L. Bartlett, Victor Gabillon, Michal Valko: A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption, in Algorithmic Learning Theory (ALT 2019) bibtex abstract talk 1 talk 2
- Xuedong Shang, Emilie Kaufmann, Michal Valko: General parallel optimization without metric, in Algorithmic Learning Theory (ALT 2019) bibtex abstract talk
- Guillaume Gautier, Rémi Bardenet, Michal Valko: Les processus ponctuels déterminantaux en apprentissage automatique bibtex abstract (Gretsi 2019)
2018
- Jean-Bastien Grill, Michal Valko, Rémi Munos: Optimistic optimization of a Brownian, in Neural Information Processing Systems (NeurIPS 2018) bibtex abstract poster
- Xuedong Shang, Emilie Kaufmann, Michal Valko: Adaptive black-box optimization got easier: HCT needs only local smoothness, in European Workshop on Reinforcement Learning (EWRL 2018) bibtex abstract poster
- Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko: Compressing the input for CNNs with the first-order scattering transform, in European Conference on Computer Vision (ECCV 2018) bibtex abstract poster
- Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric, Michal Valko: Improved large-scale graph learning through ridge spectral sparsification, in International Conference on Machine Learning (ICML 2018) bibtex abstract talk poster
- Yasin Abbasi-Yadkori, Peter L. Bartlett, Victor Gabillon, Alan Malek, Michal Valko: Best of both worlds: Stochastic & adversarial best-arm identification, Conference on Learning Theory (COLT 2018) bibtex abstract video talk poster
2017
- Daniele Calandriello, Alessandro Lazaric, Michal Valko: Efficient second-order online kernel learning with adaptive embedding, in Neural Information Processing Systems (NeurIPS 2017) bibtex abstract talk poster
- Zheng Wen, Branislav Kveton , Michal Valko, Sharan Vaswani: Online influence maximization under independent cascade model with semi-bandit feedback, in Neural Information Processing Systems (NeurIPS 2017) bibtex 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 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 talk poster
- Daniele Calandriello, Alessandro Lazaric, Michal Valko: Distributed adaptive sampling for kernel matrix approximation, in International Conference on Artificial Intelligence and Statistics (AISTATS 2017) and (ICML 2017 - LL) bibtex 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 poster
2016
- Michal Valko: Bandits on graphs and structures, habilitation thesis, École normale supérieure de Cachan (ENS Cachan 2016) bibtex 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 (NeurIPS 2016) bibtex 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 (NeurIPS 2016 - ASNMML) bibtex abstract poster
- Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yu-En L@iu: Rewards and Errors in Multi-armed Bandit for Interactive Education, in Challenges in Machine Learning: Gaming and Education workshop at Neural Information Processing Systems (NeurIPS 2016 - CIML) bibtex abstract poster
- Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard: Pliable rejection sampling, in International Conference on Machine Learning (ICML 2016) bibtex abstract talk long 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 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 poster spotlight
- Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko: Bayesian policy gradient and actor-critic algorithms, Journal of Machine Learning Research (JMLR 2016) bibtex 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 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 poster
2015
- Jean-Bastien Grill, Michal Valko, Rémi Munos: Black-box optimization of noisy functions with unknown smoothness, in Neural Information Processing Systems (NeurIPS 2015) bibtex 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 talk poster arXiv
- Manjesh Hanawal, Venkatesh Saligrama, Michal Valko, Rémi Munos: Cheap Bandits, in International Conference on Machine Learning (ICML 2015) bibtex 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 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 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 (NeurIPS 2014) bibtex abstract talk poster
- Alexandra Carpentier, Michal Valko: Extreme Bandits, in Neural Information Processing Systems (NeurIPS 2014) bibtex abstract poster
- Gergely Neu, Michal Valko: Online Combinatorial Optimization with Stochastic Decision Sets and Adversarial Losses, in Neural Information Processing Systems (NeurIPS 2014) bibtex abstract talk 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 slides poster
- Tomáš Kocák, Michal Valko, Rémi Munos, Shipra Agrawal: Spectral Thompson Sampling, in AAAI Conference on Artificial Intelligence (AAAI 2014) bibtex abstract slides poster
- Philippe Preux, Rémi Munos, Michal Valko: Bandits attack function optimization, in IEEE Congress on Evolutionary Computation (CEC 2014) bibtex 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 (NeurIPS 2014 - TCRL) bibtex 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
2013
- Michal Valko, Alexandra Carpentier, Rémi Munos: Stochastic Simultaneous Optimistic Optimization, in International Conference on Machine Learning (ICML 2013) bibtex 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 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
- 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
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 talk 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
- 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
- Michal Valko: Adaptive Graph-Based Algorithms for Conditional Anomaly Detection and Semi-Supervised Learning, PhD thesis, University of Pittsburgh (PITT 2011) bibtex 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 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 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
- 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 [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
- Michal Valko, Milos Hauskrecht: Feature importance analysis for patient management decisions in International Congress on Medical Informatics (MEDINFO 2010) bibtex 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 talk
- Michal Valko, Milos Hauskrecht: Distance metric learning for conditional anomaly detection, International Florida AI Research Society Conference (FLAIRS 2008) bibtex 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 talk
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
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
- 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
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
- Michal Valko Evolving Neural Networks for Statistical Decision Theory, Comenius University, Bratislava, 2005 (master thesis) (2005) Advisor: Radoslav Harman thesis@sk bibtex 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 (NeurIPS 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
- bibtex file with references I often use
12-Nov-2015