Hardware & devices
Driving advances in hardware, devices and cyber-physical systems.
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Deep Learning: A Review
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
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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…
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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…
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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…
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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…
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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…
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Extreme Classification in Healthcare
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…
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Extreme Multi-label Learning via Nearest Neighbor Graph Partitioning and Embedding
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…
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Active Positive Semidefinite Matrix Completion With Applications to Large Scale Bandit Problems
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…
