activity
20042020
most citedRandom Feature Maps for Dot Product Kernels

123 citations · 217 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CY2020

Analysis of Agricultural Policy Recommendations using Multi-Agent Systems

Satyandra Guthula, Sunil Simon, Harish Karnick

Despite agriculture being the primary source of livelihood for more than half of India's population, several socio-economic policies are implemented in the Indian agricultural sect…

cs.CL2019

Deep Attentive Ranking Networks for Learning to Order Sentences

Pawan Kumar, Dhanajit Brahma, Harish Karnick +1

We present an attention-based ranking framework for learning to order sentences given a paragraph. Our framework is built on a bidirectional sentence encoder and a self-attention b…

cs.CV2018

Video Colorization using CNNs and Keyframes extraction: An application in saving bandwidth

Ankur Singh, Anurag Chanani, Harish Karnick

In this paper, we tackle the problem of colorization of grayscale videos to reduce bandwidth usage. For this task, we use some colored keyframes as reference images from the colore…

cs.LG2018★ 1 cited

Bayes-optimal Hierarchical Classification over Asymmetric Tree-Distance Loss

Dheeraj Mekala, Vivek Gupta, Purushottam Kar +1

Hierarchical classification is supervised multi-class classification problem over the set of class labels organized according to a hierarchy. In this report, we study the work by R…

cs.LG2017

Leveraging Distributional Semantics for Multi-Label Learning

Rahul Wadbude, Vivek Gupta, Piyush Rai +3

We present a novel and scalable label embedding framework for large-scale multi-label learning a.k.a ExMLDS (Extreme Multi-Label Learning using Distributional Semantics). Our appro…

cs.CL2017★ 44 cited

Text Summarization using Abstract Meaning Representation

Shibhansh Dohare, Harish Karnick, Vivek Gupta

With an ever increasing size of text present on the Internet, automatic summary generation remains an important problem for natural language understanding. In this work we explore…