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Found 3 papers, 1 papers with code
Transfer Learning with Kernel Methods
In this work, we propose a transfer learning framework for kernel methods by projecting and translating the source model to the target task.
LLBoost: Last Layer Perturbation to Boost Pre-trained Neural Networks
While deep networks have produced state-of-the-art results in several domains from image classification to machine translation, hyper-parameter selection remains a significant computational bottleneck.
Optimal Transport using GANs for Lineage Tracing
In this paper, we present Super-OT, a novel approach to computational lineage tracing that combines a supervised learning framework with optimal transport based on Generative Adversarial Networks (GANs).
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