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Found 4 papers, 1 papers with code
Signed Binarization: Unlocking Efficiency Through Repetition-Sparsity Trade-Off
Efficient inference of Deep Neural Networks (DNNs) on resource-constrained edge devices is essential.
Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning
Furthermore, the intrinsic heterogeneity in human behavior can produce equally successful but disparate demonstrations, further exacerbating the challenge of discerning demonstration quality.
Signed Binary Weight Networks
Efficient inference of Deep Neural Networks (DNNs) is essential to making AI ubiquitous.
Offline Visual Representation Learning for Embodied Navigation
In this paper, we show that an alternative 2-stage strategy is far more effective: (1) offline pretraining of visual representations with self-supervised learning (SSL) using large-scale pre-rendered images of indoor environments (Omnidata), and (2) online finetuning of visuomotor representations on specific tasks with image augmentations under long learning schedules.
