Sayar Karmakar

University of Florida

PO Box 117165, 201 Stuzin Hall

Gainesville, FL 32610-0496

United States

SCHOLARLY PAPERS

9

DOWNLOADS
Rank 32,740

SSRN RANKINGS

Top 32,740

in Total Papers Downloads

2,938

SSRN CITATIONS

14

CROSSREF CITATIONS

0

Scholarly Papers (9)

1.

Understanding the Rise of Twitter-Based Cyberbullying Due to COVID-19 through Comprehensive Statistical Evaluation

In Proceedings of the 54th Hawaii International Conference on System Sciences. 2021, Maui, Hawaii (Virtual).
Number of pages: 11 Posted: 19 Jan 2021
Sayar Karmakar and Sanchari Das
University of Florida and University of Denver
Downloads 2,038 (15,021)
Citation 8

Abstract:

Loading...

COVID-19, pandemic, privacy, security, social media privacy, cyberbullying

2.

Evaluating the Impact of COVID-19 on Cyberbullying through Bayesian Trend Analysis

Proceedings of The European Interdisciplinary Cybersecurity Conference (EICC) co-located with European Cyber Week 2020
Number of pages: 6 Posted: 11 Aug 2020
Sayar Karmakar and Sanchari Das
University of Florida and University of Denver
Downloads 441 (124,801)
Citation 5

Abstract:

Loading...

cyberbullying, COVID-19, twitter, social media, time-series, change-point, bayesian, pandemic

3.

Change-Point Analysis of Cyberbullying-Related Twitter Discussions During COVID-19

Proceedings of the 16th Annual Social Informatics Research Symposium (“Sociotechnical Change Agents: ICTs, Sustainability, and Global Challenges”) in Conjunction with the 83rd Association for Information Science and Technology (ASIS&T), 2020.
Number of pages: 12 Posted: 11 Aug 2020
Sanchari Das, Andrew Kim and Sayar Karmakar
University of Denver, Indiana University Bloomington and University of Florida
Downloads 127 (414,458)

Abstract:

Loading...

twitter, cyberbullying, social media, time series, change-point, COVID-19, pandemic

4.

Bitcoin mining activity and volatility dynamics in the power market

Number of pages: 11 Posted: 05 Oct 2021
Sayar Karmakar, Riza Demirer and Rangan Gupta
University of Florida, Southern Illinois University Edwardsville - Department of Economics & Finance and University of Pretoria - Department of Economics
Downloads 103 (483,767)
Citation 3

Abstract:

Loading...

Time-varying, GARCH, Bitcoin, Electricity returns

5.

Climate Risks and Predictability of the Trading Volume of Gold:Evidence from an INGARCH Model

Number of pages: 15 Posted: 18 Oct 2022
University of Florida, University of Pretoria, Copenhagen Business School and University of Edinburgh Business School
Downloads 83 (555,175)

Abstract:

Loading...

Climate Risks, Precious Metals, Forecasting, Trading Volumes, Count Data, INGARCH

6.

Stock Market Bubbles and the Forecastability of Goldreturns (and Volatility)

Number of pages: 33 Posted: 19 Jun 2023
affiliation not provided to SSRN, University of Pretoria, University of Florida and University of Colorado Boulder
Downloads 67 (625,842)

Abstract:

Loading...

Gold, stock markets, Bubbles, forecasting, Returns, Volatility

7.

Provable Training of a ReLU Gate with an Iterative Non-Gradient Algorithm

Number of pages: 25 Posted: 10 Mar 2021 Last Revised: 04 Apr 2022
Sayar Karmakar and Anirbit Mukherjee
University of Florida and Wharton (UPenn), Department of Statistics
Downloads 52 (707,582)
Citation 2

Abstract:

Loading...

neural nets, non-gradient iterative algorithms, stochastic algorithms, non-smooth non-convex optimization

8.

Depth-2 Neural Networks Under a Data-Poisoning Attack

Number of pages: 32 Posted: 02 Aug 2022
Wharton (UPenn), Department of Statistics, University of Florida and The University of Manchester
Downloads 18 (983,961)

Abstract:

Loading...

Convolutional Neural Networks, stochastic algorithms, data poisoning, robust regression

9.

Towards Size-Independent Generalization Bounds for Deep Operator Nets

Number of pages: 37 Posted: 18 Mar 2024
affiliation not provided to SSRN, University of Florida, Indian Institute of Technology Guwahati and Wharton (UPenn), Department of Statistics
Downloads 9 (1,076,421)

Abstract:

Loading...

Rademacher complexity, DeepONets, Physics-Inspired ML, Operator Learning