no code implementations • 16 Oct 2023 • Anand Brahmbhatt, Rishi Saket, Shreyas Havaldar, Anshul Nasery, Aravindan Raghuveer
Further, the $\ell_2^2$-regressor which minimizes the loss on the aggregated dataset has a loss within $\left(1 + o(1)\right)$-factor of the optimum on the original dataset w. p.
no code implementations • 9 Jun 2023 • Anshul Nasery, Hardik Shah, Arun Sai Suggala, Prateek Jain
Our algorithm is versatile and can be used with many popular compression methods including pruning, low-rank factorization, and quantization.
no code implementations • 4 Oct 2022 • Sravanti Addepalli, Anshul Nasery, R. Venkatesh Babu, Praneeth Netrapalli, Prateek Jain
To bridge the gap between these two lines of work, we first hypothesize and verify that while SB may not altogether preclude learning complex features, it amplifies simpler features over complex ones.
no code implementations • 19 Aug 2022 • Anshul Nasery, Sravanti Addepalli, Praneeth Netrapalli, Prateek Jain
We consider the problem of OOD generalization, where the goal is to train a model that performs well on test distributions that are different from the training distribution.
1 code implementation • NeurIPS 2021 • Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, Abir De, Sunita Sarawagi
In several real world applications, machine learning models are deployed to make predictions on data whose distribution changes gradually along time, leading to a drift between the train and test distributions.
no code implementations • NAACL 2021 • Hrituraj Singh, Anshul Nasery, Denil Mehta, Aishwarya Agarwal, Jatin Lamba, Balaji Vasan Srinivasan
In this paper, we propose a novel task - MIMOQA - Multimodal Input Multimodal Output Question Answering in which the output is also multimodal.
1 code implementation • Findings (ACL) 2021 • Atul Sahay, Anshul Nasery, Ayush Maheshwari, Ganesh Ramakrishnan, Rishabh Iyer
We introduce a novel formulation that takes advantage of the syntactic grammar rules and is independent of the base system.
1 code implementation • NeurIPS 2020 • Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin
We present an algorithm that is fast enough to speed up several matrix operations.
1 code implementation • 25 Jun 2020 • Satyam Mohla, Anshul Nasery, Biplab Banerjee
Recent experiments in computer vision demonstrate texture bias as the primary reason for supreme results in models employing Convolutional Neural Networks (CNNs), conflicting with early works claiming that these networks identify objects using shape.