Statistical Learning
Dream the Impossible: Outlier Imagination with Diffusion Models
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Automating outlier data generation has thus been a long-desired alternative.
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Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
Neural Information Processing Systems
Unsurprisingly, researchers are already trying to build theoretically sound understanding of modern self-supervised representation learning methods.
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The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
Neural Information Processing Systems
However, zero-shot learning methods still require human instruction set to solve a new task.
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PAPR: Proximity Attention Point Rendering
Neural Information Processing Systems
More results and code are available on our project website.
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