Search Results for author: Amitabha Bagchi

Found 4 papers, 1 papers with code

GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks

no code implementations20 Feb 2024 Anuj Kumar Sirohi, Anjali Gupta, Sayan Ranu, Sandeep Kumar, Amitabha Bagchi

Extensive experimentation on real-world datasets showcases the efficacy of GRAPHGINI in making significant improvements in individual fairness compared to all currently available state-of-the-art methods while maintaining utility and group equality.

Fairness

Gigs with Guarantees: Achieving Fair Wage for Food Delivery Workers

1 code implementation7 May 2022 Ashish Nair, Rahul Yadav, Anjali Gupta, Abhijnan Chakraborty, Sayan Ranu, Amitabha Bagchi

With the increasing popularity of food delivery platforms, it has become pertinent to look into the working conditions of the 'gig' workers in these platforms, especially providing them fair wages, reasonable working hours, and transparency on work availability.

FROCC: Fast Random projection-based One-Class Classification

no code implementations29 Nov 2020 Arindam Bhattacharya, Sumanth Varambally, Amitabha Bagchi, Srikanta Bedathur

We present Fast Random projection-based One-Class Classification (FROCC), an extremely efficient method for one-class classification.

Classification General Classification +1

Lecture notes: Efficient approximation of kernel functions

no code implementations4 May 2020 Amitabha Bagchi

These lecture notes endeavour to collect in one place the mathematical background required to understand the properties of kernels in general and the Random Fourier Features approximation of Rahimi and Recht (NIPS 2007) in particular.

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