A5103042020- Radioactive contamination and transfer
- Radioactivity and Radon Measurements
- Optimization and Search Problems
- Nuclear Physics and Applications
- Ion-surface interactions and analysis
- Complexity and Algorithms in Graphs
- semigroups and automata theory
- Advanced Graph Theory Research
- Color Science and Applications
- Algorithms and Data Compression
- Vehicle License Plate Recognition
- Groundwater and Isotope Geochemistry
- Particle Detector Development and Performance
- Thermochemical Biomass Conversion Processes
- Atomic and Molecular Physics
- Electron and X-Ray Spectroscopy Techniques
- Radioactive element chemistry and processing
- Catalysis and Hydrodesulfurization Studies
- Catalysis for Biomass Conversion
- Atomic and Subatomic Physics Research
- Lignin and Wood Chemistry
- Petroleum Processing and Analysis
- X-ray Spectroscopy and Fluorescence Analysis
- Radiation Effects in Electronics
- Catalysis and Oxidation Reactions
ETH Zurich
2004-2023
Paul Scherrer Institute
2012
École Polytechnique Fédérale de Lausanne
2009
SINTEF
2005-2006
In the Online Delayed Connected H-Node-Deletion Problem, an unweighted graph is revealed vertex by and it must remain free of any induced copies a specific connected forbidden subgraph H at each point in time. To achieve this, algorithm must, upon occurrence H, identify irrevocably delete one or more vertices. The objective to as few vertices possible. We provide tight bounds on competitive ratio for subgraphs that do not contain two true twins false twins. further consider problem within...
Coloring is a notoriously hard problem, and even more so in the online setting, where each arriving vertex has to be colored immediately irrevocably. Already on trees, which are trivially two-colorable, it impossible achieve anything better than logarithmic competitive ratio. We show how undercut this bound by double-logarithmic factor slightly relaxed model vertices arrive random order. then also analyze algorithms with predictions, showing well we can color trees machine-learned advice of...
We analyze the competitive ratio and advice complexity of online unbounded knapsack problem. An instance is given as a sequence n items with size value each, an algorithm has to decide how often pack each item into bounded capacity. The are total packed must not exceed knapsack's capacity, while objective maximize items. While can only be once in classical 0-1 problem, version allows for multiple times. show that simple where equal its value, 2. also randomized algorithms that, contrast one...