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Found 6 papers, 1 papers with code
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
The Ising model, originally developed as a spin-glass model for ferromagnetic elements, has gained popularity as a network-based model for capturing dependencies in agents' outputs.
Boosting the Power of Kernel Two-Sample Tests
The kernel two-sample test based on the maximum mean discrepancy (MMD) is one of the most popular methods for detecting differences between two distributions over general metric spaces.
Detecting Concept Drift in the Presence of Sparsity -- A Case Study of Automated Change Risk Assessment System
In this work, we carry out a systematic study of the following: (i) different patterns of missing values, (ii) various statistical and ML based data imputation methods for different kinds of sparsity, (iii) several concept drift detection methods, (iv) practical analysis of the various drift detection metrics, (v) selecting the best concept drift detector given a dataset with missing values based on the different metrics.
Look Before You Leap! Designing a Human-Centered AI System for Change Risk Assessment
This warrants the development of an automated system to assess the risk associated with a large number of changes.
Drift-Adjusted And Arbitrated Ensemble Framework For Time Series Forecasting
We propose to employ a re-weighting based method to adjust the assigned weights to various forecasters in order to account for such distribution-drift.
Semi-Bagging Based Deep Neural Architecture to Extract Text from High Entropy Images
Furthermore, the proposed text detection method along with a text recognizer outperforms the existing state-of-the-art approaches in extracting text from high entropy images.
