We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Model checking is a suitable formal technique to analyze parallel programs' execution in an industrial context because automated tools can be designed and operated with very ...
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
Maintaining statistics on multidimensional data distributions is crucial for predicting the run-time and result size of queries and data analysis tasks with acceptable accuracy. To...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...