5 papers
Application Specific Compression of Deep Learning Models
Rohit Raj Rai, Angana Borah, Amit Awekar
Large Deep Learning models are compressed and deployed for specific applications. However, current Deep Learning model compression methods do not utilize the information about the…
Effect of dimensionality change on the bias of word embeddings
Rohit Raj Rai, Amit Awekar
Word embedding methods (WEMs) are extensively used for representing text data. The dimensionality of these embeddings varies across various tasks and implementations. The effect of…
Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy
Akshay Parekh, Ashish Anand, Amit Awekar
Large crowd-sourced datasets are often noisy and relation classification (RC) datasets are no exception. Reannotating the entire dataset is one probable solution however it is not…
Faster K-Means Cluster Estimation
Siddhesh Khandelwal, Amit Awekar
There has been considerable work on improving popular clustering algorithm `K-means' in terms of mean squared error (MSE) and speed, both. However, most of the k-means variants ten…
On Low Overlap Among Search Results of Academic Search Engines
Anasua Mitra, Amit Awekar
Number of published scholarly articles is growing exponentially. To tackle this information overload, researchers are increasingly depending on niche academic search engines. Recen…