5 citations · 7 across the 5 of their papers we have counts for
5 papers
Weighted Distillation with Unlabeled Examples
Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal +3
Distillation with unlabeled examples is a popular and powerful method for training deep neural networks in settings where the amount of labeled data is limited: A large ''teacher''…
Fast Bitmap Fit: A CPU Cache Line friendly memory allocator for single object allocations
Dhruv Matani, Gaurav Menghani
Applications making excessive use of single-object based data structures (such as linked lists, trees, etc...) can see a drop in efficiency over a period of time due to the randomi…
An Easy-to-Use-and-Deploy Grid Computing Framework
Gaurav Menghani, Anil Harwani, Yash Londhe +1
A few grid-computing tools are available for public use. However, such systems are usually quite complex and require several man-months to set up. In case the user wishes to set-up…
Genome Compression Against a Reference
Anirduddha Laud, Gaurav Menghani, Madhava Keralapura
Being able to store and transmit human genome sequences is an important part in genomic research and industrial applications. The complete human genome has 3.1 billion base pairs (…
Learning from a Teacher using Unlabeled Data
Gaurav Menghani, Sujith Ravi
Knowledge distillation is a widely used technique for model compression. We posit that the teacher model used in a distillation setup, captures relationships between classes, that…