misovalko/my-research-papers
Michal Valko Research Papers Selected research papers by Michal Valko on bandits, reinforcement learning, and online learning. Papers Spectral bandits for smooth graph functions with applications in recommender systems Conditional anomaly detection methods for patient-management alert systems Learning predictive models for combinations of heterogeneous proteomic data sources Outlier detection for patient monitoring and alerting Conditional outlier detection for… See the full description on the dataset page: https://huggingface.co/datasets/misovalko/my-research-papers.
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Michal Valko Research Papers
Selected research papers by Michal Valko on bandits, reinforcement learning, and online learning.
Papers
- Spectral bandits for smooth graph functions with applications in recommender systems
- Conditional anomaly detection methods for patient-management alert systems
- Learning predictive models for combinations of heterogeneous proteomic data sources
- Outlier detection for patient monitoring and alerting
- Conditional outlier detection for clinical alerting
- Evidence-based anomaly detection in clinical domains
- Feature importance analysis for patient management decisions
- Bandits on graphs and structures
- Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning
- Bandits attack function optimization
- Active multiple matrix completion with adaptive confidence sets
- Middle-mile logistics through the lens of goal-conditioned reinforcement learning
- Black-box optimization of noisy functions with unknown smoothness
- Trading off rewards and errors in multi-armed bandits
- Revealing graph bandits for maximizing local influence
- Distance metric learning for conditional anomaly detection
- Bayesian policy gradient and actor-critic algorithms
- Online semi-supervised perception: Real-time learning without explicit feedback
- Learning from a single labeled face and a stream of unlabeled data
- Semi-supervised learning with max-margin graph cuts
- Evolutionary feature selection for spiking neural network pattern classifiers
- Large-scale semi-supervised learning with online spectral graph sparsification
- Online learning with Erdős-Rényi side-observation graphs
- Online combinatorial optimization with stochastic decision sets and adversarial losses
- Spectral bandits
- Efficient learning by implicit exploration in bandit problems with side observations
- Extreme bandits
- Stochastic simultaneous optimistic optimization
- Conditional anomaly detection using soft harmonic functions: An application to clinical alerting
- Pliable rejection sampling
- Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
- Conditional anomaly detection with soft harmonic functions
- A single algorithm for both restless and rested rotting bandits
- Maximum entropy semi-supervised inverse reinforcement learning
- Analysis of Nyström method with sequential ridge leverage scores
- Improved large-scale graph learning through ridge spectral sparsification
- Planning in entropy-regularized Markov decision processes and games
- On two ways to use determinantal point processes for Monte Carlo integration
- Budgeted online influence maximization