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cs.LG2025
Adapting to Fragmented and Evolving Data: A Fisher Information Perspective
Behraj Khan, Tahir Qasim Syed, Nouman Muhammad Durrani
Modern machine learning systems operating in dynamic environments often face \textit{sequential covariate shift} (SCS), where input distributions evolve over time while the conditi…
cs.LG2025
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization
Behraj Khan, Behroz Mirza, Nouman Durrani +1
The continuous surge in data volume and velocity is often dealt with using data orchestration and distributed processing approaches, abstracting away the machine learning challenge…
cs.LG2024
Mitigating covariate shift in non-colocated data with learned parameter priors
Behraj Khan, Behroz Mirza, Nouman Durrani +1
When training data are distributed across{ time or space,} covariate shift across fragments of training data biases cross-validation, compromising model selection and assessment. W…