activity
20092021
most citedCounterfactual Estimation and Optimization of Click Metrics for Search Engines

18 citations · 34 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Unsupervised Contextualized Document Representation

Ankur Gupta, Vivek Gupta

Several NLP tasks need the effective representation of text documents. Arora et. al., 2017 demonstrate that simple weighted averaging of word vectors frequently outperforms neural…

cs.CL2021

BreakingBERT@IITK at SemEval-2021 Task 9 : Statement Verification and Evidence Finding with Tables

Aditya Jindal, Ankur Gupta, Jaya Srivastava +4

Recently, there has been an interest in factual verification and prediction over structured data like tables and graphs. To circumvent any false news incident, it is necessary to n…

cs.SI2021★ 9 cited

TruthBot: An Automated Conversational Tool for Intent Learning, Curated Information Presenting, and Fake News Alerting

Ankur Gupta, Yash Varun, Prarthana Das +5

We present TruthBot, an all-in-one multilingual conversational chatbot designed for seeking truth (trustworthy and verified information) on specific topics. It helps users to obtai…

cs.LG2014★ 18 cited

Counterfactual Estimation and Optimization of Click Metrics for Search Engines

Lihong Li, Shunbao Chen, Jim Kleban +1

Optimizing an interactive system against a predefined online metric is particularly challenging, when the metric is computed from user feedback such as clicks and payments. The key…

cs.DS2012★ 7 cited

Near-Optimal Online Multiselection in Internal and External Memory

Jérémy Barbay, Ankur Gupta, S. Srinivasa Rao +1

We introduce an online version of the multiselection problem, in which q selection queries are requested on an unsorted array of n elements. We provide the first online algorithm t…

cs.DS2009

Online Sorting via Searching and Selection

Ankur Gupta, Anna Kispert, Jonathan P. Sorenson

In this paper, we present a framework based on a simple data structure and parameterized algorithms for the problems of finding items in an unsorted list of linearly ordered items…