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Deep Structured Prediction is a type of machine learning that leverages deep neural networks to predict structured outputs such as sequences, parse trees, or other structured objects. It combines the power of deep learning with the ability to make complex predictions that require understanding of the structure of the data. Deep Structured Prediction can be used for a variety of tasks, such as natural language processing, computer vision, and robotics.
... Scaling Matters in Deep Structured-Prediction Models by Aleksandr Shevchenko et ...
... prediction, deep learning Martin Jaggi, EPFL, Switzerland Distributed training, federated learning, optimization Prateek Jain, Microsoft Research, India Non-convex Optimization, Stochastic Optimization, Large-scale Optimization, Resource-constrained Machine Learning Stefanie Jegelka, ...
... Another notable work is the Deep Structured Prediction for Facial Landmark Detection, which combines a deep CNN with a Conditional Random Field to explicitly embed the structural dependencies among landmark points. Practical applications of facial landmark detection can be found in various ...
... structured prediction, amortized inference, PAC theory for inference, multi-task structured prediction, and integrating deep learning techniques with structured prediction frameworks); and point to fertile areas of research from both technical and application point of view. ...
... In Deep RL Meets Structured Prediction Workshop at ICLR https://openreview.net/forum?id=r1lgTGL5DE Kool, W., van Hoof, H., & Welling, M. (2019). Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. Proceedings of Machine Learning ...