10 citations · 18 across the 6 of their papers we have counts for
7 papers
Semi-supervised Learning for Marked Temporal Point Processes
Shivshankar Reddy, Anand Vir Singh Chauhan, Maneet Singh +1
Temporal Point Processes (TPPs) are often used to represent the sequence of events ordered as per the time of occurrence. Owing to their flexible nature, TPPs have been used to mod…
CIKM AnalytiCup 2017 Lazada Product Title Quality Challenge An Ensemble of Deep and Shallow Learning to predict the Quality of Product Titles
Karamjit Singh, Vishal Sunder
We present an approach where two different models (Deep and Shallow) are trained separately on the data and a weighted average of the outputs is taken as the final result. For the…
Crop Planning using Stochastic Visual Optimization
Gunjan Sehgal, Bindu Gupta, Kaushal Paneri +3
As the world population increases and arable land decreases, it becomes vital to improve the productivity of the agricultural land available. Given the weather and soil properties,…
Comparative Benchmarking of Causal Discovery Techniques
Karamjit Singh, Garima Gupta, Vartika Tewari +1
In this paper we present a comprehensive view of prominent causal discovery algorithms, categorized into two main categories (1) assuming acyclic and no latent variables, and (2) a…
Minimally-Supervised Attribute Fusion for Data Lakes
Karamjit Singh, Garima Gupta, Gautam Shroff +1
Aggregate analysis, such as comparing country-wise sales versus global market share across product categories, is often complicated by the unavailability of common join attributes,…
Deep Convolutional Neural Networks for Pairwise Causality
Karamjit Singh, Garima Gupta, Lovekesh Vig +2
Discovering causal models from observational and interventional data is an important first step preceding what-if analysis or counterfactual reasoning. As has been shown before, th…