most citedInterpretable Multi-Head Self-Attention model for Sarcasm Detection in social media

42 citations · 47 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CY20213 cited

Audit and Assurance of AI Algorithms: A framework to ensure ethical algorithmic practices in Artificial Intelligence

Ramya Akula, Ivan Garibay

Algorithms are becoming more widely used in business, and businesses are becoming increasingly concerned that their algorithms will cause significant reputational or financial dama…

cs.CY2021

Ethical AI for Social Good

Ramya Akula, Ivan Garibay

The concept of AI for Social Good(AI4SG) is gaining momentum in both information societies and the AI community. Through all the advancement of AI-based solutions, it can solve soc…

cs.CL202142 cited

Interpretable Multi-Head Self-Attention model for Sarcasm Detection in social media

Ramya Akula, Ivan Garibay

Sarcasm is a linguistic expression often used to communicate the opposite of what is said, usually something that is very unpleasant with an intention to insult or ridicule. Inhere…

cs.PF20191 cited

System Performance with varying L1 Instruction and Data Cache Sizes: An Empirical Analysis

Ramya Akula, Kartik Jain, Deep Jigar Kotecha

In this project, we investigate the fluctuations in performance caused by changing the Instruction (I-cache) size and the Data (D-cache) size in the L1 cache. We employ the Gem5 fr…

cs.LG2019

Forecasting the Success of Television Series using Machine Learning

Ramya Akula, Zachary Wieselthier, Laura Martin +1

Television is an ever-evolving multi billion dollar industry. The success of a television show in an increasingly technological society is a vast multi-variable formula. The art of…

cs.LG2019

Supervised Machine Learning based Ensemble Model for Accurate Prediction of Type 2 Diabetes

Ramya Akula, Ni Nguyen, Ivan Garibay

According to the American Diabetes Association(ADA), 30.3 million people in the United States have diabetes, but only 7.2 million may be undiagnosed and unaware of their condition.…