3 citations · 5 across the 4 of their papers we have counts for
13 papers
Delaytron: Efficient Learning of Multiclass Classifiers with Delayed Bandit Feedbacks
Naresh Manwani, Mudit Agarwal
In this paper, we present online algorithm called {\it Delaytron} for learning multi class classifiers using delayed bandit feedbacks. The sequence of feedback delays $\{d_t\}_{t=1…
RISAN: Robust Instance Specific Abstention Network
Bhavya Kalra, Kulin Shah, Naresh Manwani
In this paper, we propose deep architectures for learning instance specific abstain (reject option) binary classifiers. The proposed approach uses double sigmoid loss function as d…
Multiclass Classification using dilute bandit feedback
Gaurav Batra, Naresh Manwani
This paper introduces a new online learning framework for multiclass classification called learning with diluted bandit feedback. At every time step, the algorithm predicts a candi…
Robust Deep Ordinal Regression Under Label Noise
Bhanu Garg, Naresh Manwani
The real-world data is often susceptible to label noise, which might constrict the effectiveness of the existing state of the art algorithms for ordinal regression. Existing works…
Online Algorithms for Multiclass Classification using Partial Labels
Rajarshi Bhattacharjee, Naresh Manwani
In this paper, we propose online algorithms for multiclass classification using partial labels. We propose two variants of Perceptron called Avg Perceptron and Max Perceptron to de…
Expert2Coder: Capturing Divergent Brain Regions Using Mixture of Regression Experts
Subba Reddy Oota, Naresh Manwani, Raju S. Bapi
fMRI semantic category understanding using linguistic encoding models attempts to learn a forward mapping that relates stimuli to the corresponding brain activation. State-of-the-a…