7 citations · 14 across the 5 of their papers we have counts for
6 papers
Fairness in Rating Prediction by Awareness of Verbal and Gesture Quality of Public Speeches
Ankani Chattoraj, Rupam Acharyya, Shouman Das +2
The role of verbal and non-verbal cues towards great public speaking has been a topic of exploration for many decades. We identify a commonality across present theories, the elemen…
Statistical Mechanical Analysis of Neural Network Pruning
Rupam Acharyya, Ankani Chattoraj, Boyu Zhang +2
Deep learning architectures with a huge number of parameters are often compressed using pruning techniques to ensure computational efficiency of inference during deployment. Despit…
Detection and Mitigation of Bias in Ted Talk Ratings
Rupam Acharyya, Shouman Das, Ankani Chattoraj +2
Unbiased data collection is essential to guaranteeing fairness in artificial intelligence models. Implicit bias, a form of behavioral conditioning that leads us to attribute predet…
To be or not to be? A spatial predictive crime model for Rochester
Ankani Chattoraj, Rupam Acharyya, Sabyasachi Shivkumar +2
This project uses a spatial model (Geographically Weighted Regression) to relate various physical and social features to crime rates. Besides making interesting predictions from ba…
FairyTED: A Fair Rating Predictor for TED Talk Data
Rupam Acharyya, Shouman Das, Ankani Chattoraj +1
With the recent trend of applying machine learning in every aspect of human life, it is important to incorporate fairness into the core of the predictive algorithms. We address the…
A probabilistic population code based on neural samples
Sabyasachi Shivkumar, Richard D. Lange, Ankani Chattoraj +1
Sensory processing is often characterized as implementing probabilistic inference: networks of neurons compute posterior beliefs over unobserved causes given the sensory inputs. Ho…