The IJCAI-09 Workshop on Machine Learning and AI Applications in Astrophysics and Cosmology

Pasadena, California, July 16 - 17, 2009

Presentations:

• Djorgovski: Setting the stage: the goals of the workshop
• Ball: Data Mining and Machine Learning in Astronomy
• Borne: The VO and Large Surveys: What More Do We Need?
• Longo: Astronomical data mining: Renaissance or dark age?
• Connolly: Scaling Up and Scaling Out
• Myers: The Death of Spectroscopy
• Mahabal: Combining diverse classifiers in the time domain
• Khardon: From Raw Measurements to Clean Catalogs: Automatic Filtering and Classification of Variable Stars in the MACHO Survey
• Wozniak: Mining the sky in real time
• Babu: Understanding 21st Century Astronomical Data Cubes
• van Dyk: Astrostatistics: Complex Models and Complex Questions
• Schneider: Active Learning for Fitting Simulations to Observational Data
• Jojic: Could existing computer vision tools assist/replace humans in the Galaxy Zoo?
• Kubica: Scaling up Data Streams for Asteroid Tracking
• Roweis: Making The Sky Searchable: Large Scale Astronomical Pattern Recognition
• Freeman: Measurement Error and Estimator Bias
• Lee: High-dimensional Inference for Large Data Sets
• Sen: Separating Signal from Background
• Graham: Philosophical Languages in the 21st Century
• Gil & Deelman: Semantic Workflow Reasoning for Scientific Data Analysis
• Gray: Machine learning on massive datasets