2 papers
astro-ph.EP2026
PERTURB-c: Correlation Aware Perturbation Explainability for Regression Techniques to Understand Retrieval Black-boxes
Jools D. Clarke, Gordon Yip, Nikolaos Nikolaou
In this paper we introduce PERTURB-c, a correlation-aware framework for interpreting black box regression models with one-dimensional structured inputs. We demonstrate this framewo…
cs.LG2024
Efficient Model Compression Techniques with FishLeg
Jamie McGowan, Wei Sheng Lai, Weibin Chen +7
In many domains, the most successful AI models tend to be the largest, indeed often too large to be handled by AI players with limited computational resources. To mitigate this, a…