Gem-Miner: Finding Lottery Tickets at Initialization and Bettering All Baselines at 19x Faster Speeds

In the new paper Rare Gems: Finding Lottery Tickets at Initialization, a research team from Carnegie Mellon University, MBZUAI, Petuum, Inc and the University of Wisconsin-Madison proposes GEM-MINER, an algorithm that finds sparse subnetworks at initialization trainable to accuracy that is comparable or better than iterative magnitude pruning (IMP) with warm-up.

ai artificial intelligence deep-neural-networks machine learning machine learning & data science ml model-pruning research technology