Low-resource Morphological Generation with Neural Sequence-to-Sequence Models
Explore neural sequence-to-sequence approaches for morphological generation in low-resource languages, including multi-task learning, cross-lingual transfer, and semi-supervised techniques.
Ads Ranking Evolution at Pinterest - From Logistic Regression to Deep Learning
Explore Pinterest's ads ranking evolution, from logistic regression to deep learning transformers, incorporating sequential signals and multi-task learning. Gain insights on overcoming challenges and advancing ML platforms.
Large Scale Pathways Recommender Systems (PaRS) at Verizon
Explore Verizon's innovative multi-task learning recommender system, PaRS, leveraging Ray ecosystem to enhance customer experience through deep learning and efficient large-scale model training.
A View in Old and New Machine Learning
Explore old and new machine learning approaches, comparing hierarchical probabilistic models with deep neural networks and examining their unique capabilities and potential combinations.
Generative Sequence Models for Sequential Decision Making
Explore generative sequence models for decision-making under uncertainty. Learn how Transformer architecture and language modeling advances can enhance offline learning, online exploration, and multi-task generalization in AI.