no code implementations • 7 Nov 2020 • Aashi Jindal, Prashant Gupta, Debarka Sengupta, Jayadeva
We propose Enhash, a fast ensemble learner that detects \textit{concept drift} in a data stream.
1 code implementation • 14 May 2020 • Joydip Dhar, Ashaya Shukla, Mukul Kumar, Prashant Gupta
kNN is a very effective Instance based learning method, and it is easy to implement.
no code implementations • 2 Sep 2019 • Prashant Gupta, Aashi Jindal, Jayadeva, Debarka Sengupta
We present a new way of constructing an ensemble classifier, named the Guided Random Forest (GRAF) in the sequel.
no code implementations • WS 2019 • Hemant Pugaliya, Karan Saxena, Shefali Garg, Sheetal Shalini, Prashant Gupta, Eric Nyberg, Teruko Mitamura
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 margin.