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Found 5 papers, 0 papers with code
Harnessing Geometric Constraints from Emotion Labels to improve Face Verification
For the task of face verification, we explore the utility of harnessing auxiliary facial emotion labels to impose explicit geometric constraints on the embedding space when training deep embedding models.
Error Autocorrelation Objective Function for Improved System Modeling
Deep learning models are trained to minimize the error between the model's output and the actual values.
Toward Automated Classroom Observation: Multimodal Machine Learning to Estimate CLASS Positive Climate and Negative Climate
In this work we present a multi-modal machine learning-based system, which we call ACORN, to analyze videos of school classrooms for the Positive Climate (PC) and Negative Climate (NC) dimensions of the CLASS observation protocol that is widely used in educational research.
Improved Modeling of Complex Systems Using Hybrid Physics/Machine Learning/Stochastic Models
Combining domain knowledge models with neural models has been challenging.
Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth
In particular: (1) We show that if the true correlation between $U$ and $V$ is $r$, then the expected sample correlation, over all vectors $\mathcal{T}^n$ whose correlation with $U$ is $q$, is $qr$.
