Asia
Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly
Large language and vision models have been leading a revolution in visual computing. By greatly scaling up sizes of data and model parameters, the large models learn deep priors which lead to remarkable performance in various tasks.
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
Dylan J. Foster, Akshay Krishnamurthy
Neural Information Processing Systems http://nips.cc/
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
Estimating the generalization performance is practically challenging on out-of-distribution (OOD) data without ground-truth labels.
Multi-ObjectiveDeepLearning withAdaptiveReferenceVectors
Many deep learning models involve optimizing multiple objectives. Since objectives are often conflicting, we aim to get diverse and representative trade-off solutions among these objectives.
Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks
Neural Information Processing Systems http://nips.cc/
