21 citations · 32 across the 12 of their papers we have counts for
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cs.LG2025
Explore the Loss space with Hill-ADAM
Meenakshi Manikandan, Leilani Gilpin
This paper introduces Hill-ADAM. Hill-ADAM is an optimizer with its focus towards escaping local minima in prescribed loss landscapes to find the global minimum. Hill-ADAM escapes…
cs.LG2023★ 1 cited
A novel post-hoc explanation comparison metric and applications
Shreyan Mitra, Leilani Gilpin
Explanatory systems make the behavior of machine learning models more transparent, but are often inconsistent. To quantify the differences between explanatory systems, this paper p…
cs.LG2023★ 2 cited
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa, Leilani H. Gilpin, Roberto Capobianco
Compositional Explanations is a method for identifying logical formulas of concepts that approximate the neurons' behavior. However, these explanations are linked to the small spec…