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Found 5 papers, 0 papers with code
Augmenting Decision Making via Interactive What-If Analysis
The fundamental goal of business data analysis is to improve business decisions using data.
Stochastic Package Queries in Probabilistic Databases
We provide methods for specifying -- via a SQL extension -- and processing stochastic package queries (SPQs), in order to solve optimization problems over uncertain data, right where the data resides.
Decision Making
Decision Making Under Uncertainty
+1
Databases
Temporally-Biased Sampling Schemes for Online Model Management
To maintain the accuracy of supervised learning models in the presence of evolving data streams, we provide temporally-biased sampling schemes that weight recent data most heavily, with inclusion probabilities for a given data item decaying over time according to a specified "decay function".
Unknown Examples & Machine Learning Model Generalization
Over the past decades, researchers and ML practitioners have come up with better and better ways to build, understand and improve the quality of ML models, but mostly under the key assumption that the training data is distributed identically to the testing data.
Temporally-Biased Sampling for Online Model Management
Moreover, time-biasing lets the models adapt to recent changes in the data while -- unlike in a sliding-window approach -- still keeping some old data to ensure robustness in the face of temporary fluctuations and periodicities in the data values.
Databases
