This work proposes a disentanglement-based intervention framework, termed IB-ACT, that identifies both where and how to intervene by exploiting the layer-wise geometry of representation spaces to isolate behavior-relevant information without disturbing other dimensions, and introduces a layer-selection mechanism determ...
Toan Doan, Thin Nguyen, Sunil Gupta· Proceedings of the 32nd ACM...· 0 citations
Sample size determination for machine learning (ML) prediction models is challenging because conventional power analysis typically requires the predictor-outcome relationship and effect structure to be specified a priori. Nonlinear ML models learn complex prediction surfaces that do not admit straightforward analytical...
Dat Phan-Trong, Sunil Gupta, S. Venkatesh· 0 citations
This work proposes a disentanglement-based intervention framework, termed IB-ACT, that identifies both where and how to intervene by exploiting the layer-wise geometry of representation spaces to isolate behavior-relevant information without disturbing other dimensions, and introduces a layer-selection mechanism determ...
Toan Doan, Thin Nguyen, Sunil Gupta· Proceedings of the 32nd ACM...· 0 citations
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