no code implementations • 20 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.
1 code implementation • 7 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.
no code implementations • 29 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.
no code implementations • 4 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.