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Found 5 papers, 3 papers with code
Causal Estimation of User Learning in Personalized Systems
In online platforms, the impact of a treatment on an observed outcome may change over time as 1) users learn about the intervention, and 2) the system personalization, such as individualized recommendations, change over time.
BAM: Bayes with Adaptive Memory
Online learning via Bayes' theorem allows new data to be continuously integrated into an agent's current beliefs.
Rethinking Evaluation Methodology for Audio-to-Score Alignment
This paper offers a precise, formal definition of an audio-to-score alignment.
Sound Audio and Speech Processing
Dynamic Tensor Rematerialization
Checkpointing enables the training of deep learning models under restricted memory budgets by freeing intermediate activations from memory and recomputing them on demand.
Estimating the number and effect sizes of non-null hypotheses
We study the problem of estimating the distribution of effect sizes (the mean of the test statistic under the alternate hypothesis) in a multiple testing setting.
