3 citations · 10 across the 7 of their papers we have counts for
8 papers
Prediction of the disease controllability in a complex network using machine learning algorithms
Richa Tripathi, Amit Reza, Dinesh Garg
The application of machine learning (ML) techniques span a vast spectrum ranging from speech, face and character recognition, medical diagnosis, anomaly detection in data to the ge…
Deep Domain Adaptation under Deep Label Scarcity
Amar Prakash Azad, Dinesh Garg, Priyanka Agrawal +1
The goal behind Domain Adaptation (DA) is to leverage the labeled examples from a source domain so as to infer an accurate model in a target domain where labels are not available o…
Improved Linear Embeddings via Lagrange Duality
Kshiteej Sheth, Dinesh Garg, Anirban Dasgupta
Near isometric orthogonal embeddings to lower dimensions are a fundamental tool in data science and machine learning. In this paper, we present the construction of such embeddings…
A Sparse Nonlinear Classifier Design Using AUC Optimization
Vishal Kakkar, Shirish K. Shevade, S Sundararajan +1
AUC (Area under the ROC curve) is an important performance measure for applications where the data is highly imbalanced. Learning to maximize AUC performance is thus an important r…
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds
Divya Padmanabhan, Satyanath Bhat, Dinesh Garg +2
We study the problem of training an accurate linear regression model by procuring labels from multiple noisy crowd annotators, under a budget constraint. We propose a Bayesian mode…
Greedy Block Coordinate Descent (GBCD) Method for High Dimensional Quadratic Programs
Gugan Thoppe, Vivek S. Borkar, Dinesh Garg
High dimensional unconstrained quadratic programs (UQPs) involving massive datasets are now common in application areas such as web, social networks, etc. Unless computational reso…