Visual Understanding in Natural Language
Bridging visual and natural language understanding is a fundamental requirement for intelligent agents. This talk will focus mainly on automatic image captioning and visual question answering (VQA). I will cover some recent advances in automatic…
Acoustic-To-Word Model Without OOV
Dreaming Contextual Memory
Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document…
Deep Learning Approach for Extreme Multi-label Text Classification
Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document…
EZLearn: Exploiting Organic Supervision in Large-Scale Data Annotation
Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document…
Precision-Recall versus Accuracy and the Role of Large Data Sets
Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document…
A Reduction Principle for Generalizing Bona Fide Risk Bounds in Multi-class Setting
Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document…