40 citations · 75 across the 6 of their papers we have counts for
7 papers
Neural Cross-Domain Collaborative Filtering with Shared Entities
Vijaikumar M, Shirish Shevade, M N Murty
Cross-Domain Collaborative Filtering (CDCF) provides a way to alleviate data sparsity and cold-start problems present in recommendation systems by exploiting the knowledge from rel…
Deep Learning for Bug-Localization in Student Programs
Rahul Gupta, Aditya Kanade, Shirish Shevade
Providing feedback is an integral part of teaching. Most open online courses on programming make use of automated grading systems to support programming assignments and give real-t…
A framework for the extraction of Deep Neural Networks by leveraging public data
Soham Pal, Yash Gupta, Aditya Shukla +3
Machine learning models trained on confidential datasets are increasingly being deployed for profit. Machine Learning as a Service (MLaaS) has made such models easily accessible to…
Deep Reinforcement Learning for Programming Language Correction
Rahul Gupta, Aditya Kanade, Shirish Shevade
Novice programmers often struggle with the formal syntax of programming languages. To assist them, we design a novel programming language correction framework amenable to reinforce…
Topic Model Based Multi-Label Classification from the Crowd
Divya Padmanabhan, Satyanath Bhat, Shirish Shevade +1
Multi-label classification is a common supervised machine learning problem where each instance is associated with multiple classes. The key challenge in this problem is learning th…
Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses
Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, Shirish Shevade
Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarch…