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factor of 1000, opening the road for gigapixel image generation at no additional cost. Our cascading method uses the image generated at the lowest resolution as a
In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to sample images at higher-resolutions with a single GPU.
Fighting Boredom in Recommender Systems with Linear Reinforcement Learning
Romain WARLOP, Alessandro Lazaric, Jérémie Mary
We argue that this assumption is rarely verified in practice, as the recommendation process itself may impact the user's preferences.
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
We compare the algorithms on a wide range of large, convolutional and transformer-based neural network architectures.
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk
Shuang Li, Gongguo Tang, Michael B. Wakin
Neural Information Processing Systems http://nips.cc/
Are sample means in multi-armed bandits positively or negatively biased?
Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
Neural Information Processing Systems http://nips.cc/
Battle of the Backbones
Diffusion backbone, across a diverse set of computer vision tasks ranging from classification to object detection to OOD generalization and more.