Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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The Cambridge Law Corpus: A Dataset for Legal AI Research
Neural Information Processing Systems
We introduce the Cambridge Law Corpus (CLC), a corpus for legal AI research.
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ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splatting
Neural Information Processing Systems
Omnidirectional (or 360-degree) images are increasingly being used for 3D applications since they allow the rendering of an entire scene with a single image.
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LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
Neural Information Processing Systems
Y et, their massive memory consumption has become a significant roadblock to large-scale training.
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Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities
Neural Information Processing Systems
DNN to represent the collaboration between a set of input variables.
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Y otam Alexander *, Nimrod De La Vega
Neural Information Processing Systems
The question of what makes a data distribution suitable for deep learning is a fundamental open problem.
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