Peste, Alexandra

8 publications

TMLR 2024 Accurate Neural Network Pruning Requires Rethinking Sparse Optimization Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh

CVPR 2023 Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures Eugenia Iofinova, Alexandra Peste, Dan Alistarh

ICLR 2023 CrAM: A Compression-Aware Minimizer Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H Lampert, Dan Alistarh

NeurIPS 2023 Knowledge Distillation Performs Partial Variance Reduction Mher Safaryan, Alexandra Peste, Dan Alistarh

CVPR 2022 How Well Do Sparse ImageNet Models Transfer? Eugenia Iofinova, Alexandra Peste, Mark Kurtz, Dan Alistarh

NeurIPS 2021 AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh

NeurIPSW 2021 SSSE: Efficiently Erasing Samples from Trained Machine Learning Models Alexandra Peste, Dan Alistarh, Christoph H Lampert

JMLR 2021 Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste