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On learning latent models with multi-instance weak supervision
We consider a weakly supervised learning scenario where the supervision signal is
generated by a transition function $\sigma $ of labels associated with multiple input …
generated by a transition function $\sigma $ of labels associated with multiple input …
Discrete latent structure in neural networks
Many types of data from fields including natural language processing, computer vision, and
bioinformatics, are well represented by discrete, compositional structures such as trees …
bioinformatics, are well represented by discrete, compositional structures such as trees …
On Characterizing and Mitigating Imbalances in Multi-Instance Partial Label Learning
* Multi-Instance Partial Label Learning*(MI-PLL) is a weakly-supervised learning setting
encompassing* partial label learning*,* latent structural learning*, and* neurosymbolic …
encompassing* partial label learning*,* latent structural learning*, and* neurosymbolic …
Moment distributionally robust tree structured prediction
Structured prediction of tree-shaped objects is heavily studied under the name of syntactic
dependency parsing. Current practice based on maximum likelihood or margin is either …
dependency parsing. Current practice based on maximum likelihood or margin is either …
Learning Structured Models with Weak Supervision
K Wang - 2024 - repository.upenn.edu
Over the past decade, the remarkable success of machine learning in various fields has
highlighted the critical role of substantial quantities of training data, thereby bringing both the …
highlighted the critical role of substantial quantities of training data, thereby bringing both the …
[ספר][B] From Enormous Structured Models to On-device Federated Learning: Robustness, Heterogeneity and Optimization
K Pillutla - 2022 - search.proquest.com
Artificial intelligence has been shaped by three revolutions in recent years:(1) differentiable
programming, the practice of writing programs by chaining parameterized modules and …
programming, the practice of writing programs by chaining parameterized modules and …