6 citations · 7 across the 3 of their papers we have counts for
3 papers
Enhash: A Fast Streaming Algorithm For Concept Drift Detection
Aashi Jindal, Prashant Gupta, Debarka Sengupta +1
We propose Enhash, a fast ensemble learner that detects \textit{concept drift} in a data stream. A stream may consist of abrupt, gradual, virtual, or recurring events, or a mixture…
A Weighted Mutual k-Nearest Neighbour for Classification Mining
Joydip Dhar, Ashaya Shukla, Mukul Kumar +1
kNN is a very effective Instance based learning method, and it is easy to implement. Due to heterogeneous nature of data, noises from different possible sources are also widespread…
Pentagon at MEDIQA 2019: Multi-task Learning for Filtering and Re-ranking Answers using Language Inference and Question Entailment
Hemant Pugaliya, Karan Saxena, Shefali Garg +4
Parallel deep learning architectures like fine-tuned BERT and MT-DNN, have quickly become the state of the art, bypassing previous deep and shallow learning methods by a large marg…