3 papers
cs.AI2026
Accuracy and Robustness of Model Cascades Under Data Perturbations
Pallavi Mitra, Jai Kushwaha, Felix Biessmann
Prediction cascades significantly reduce energy consumption of Artificial Intelligence (AI) models while maintaining high predictive performance. The idea is that easy inputs are r…
cs.LG2024
Automated Computational Energy Minimization of ML Algorithms using Constrained Bayesian Optimization
Pallavi Mitra, Felix Biessmann
Bayesian optimization (BO) is an efficient framework for optimization of black-box objectives when function evaluations are costly and gradient information is not easily accessible…
cs.CV2024
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
Pallavi Mitra, Gesina Schwalbe, Nadja Klein
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many computer vision tasks. However, high computational and storage demands hinder their deployme…