Social Network Model Based on Keyword Categorization. - Prantik Bhattacharyya; Ankush Garg; Shyhtsun Felix Wu (ASONAM, 2009)

Information Flow and Search in Unstructured Keyword Based Social Networks. - Ankush Garg; Prantik Bhattacharyya; Charles U. Martel; Shyhtsun Felix Wu (CSE (4), 2009)

Design and Implementation of Davis Social Links OSN Kernel. - Thomas Tran; Kelcey Chan; Shaozhi Ye; Prantik Bhattacharyya; Ankush Garg; Xiaoming Lu; Shyhtsun Felix Wu (WASA, 2009)

Analysis of user keyword similarity in online social networks. - Prantik Bhattacharyya; Ankush Garg; Shyhtsun Felix Wu (Soc. Netw. Anal. Min., 2011)

GROOV: A geographic routing over VANETs and its performance evaluation. - Sanjay K. Dhurandher; Mohammad S. Obaidat; Deepti Bhardwaj; Ankush Garg (GLOBECOM, 2012)

Wormhole attack prevention using clustering and digital signatures in reactive routing. - Amarjit Malhotra; Deepti Bhardwaj; Ankush Garg (ICNSC, 2012)

Progressive alignment using Shortest Common Supersequence. - Ankush Garg; Deepak Garg 002 (ICACCI, 2014)

Machine Translation: A Literature Review. - Ankush Garg; Mayank Agarwal (CoRR, 2019)

Echo State Neural Machine Translation. - Ankush Garg; Yuan Cao; Qi Ge (CoRR, 2020)

Echo State Speech Recognition. - Harsh Shrivastava 001; Ankush Garg; Yuan Cao 007; Yu Zhang 033; Tara N. Sainath (ICASSP, 2021)

The geometry of integration in text classification RNNs. - Kyle Aitken; Vinay Venkatesh Ramasesh; Ankush Garg; Yuan Cao; David Sussillo; Niru Maheswaranathan (ICLR, 2021)

Efficient and Private Federated Learning with Partially Trainable Networks. - Hakim Sidahmed; Zheng Xu 002; Ankush Garg; Yuan Cao; Mingqing Chen (CoRR, 2021)

A Loss Curvature Perspective on Training Instability in Deep Learning. - Justin Gilmer; Behrooz Ghorbani; Ankush Garg; Sneha Kudugunta; Behnam Neyshabur; David Cardoze; George E. Dahl; Zachary Nado; Orhan Firat (CoRR, 2021)

A Loss Curvature Perspective on Training Instabilities of Deep Learning Models. - Justin Gilmer; Behrooz Ghorbani; Ankush Garg; Sneha Kudugunta; Behnam Neyshabur; David Cardoze; George Edward Dahl; Zachary Nado; Orhan Firat (ICLR, 2022)

Data Scaling Laws in NMT: The Effect of Noise and Architecture. - Yamini Bansal; Behrooz Ghorbani; Ankush Garg; Biao Zhang 006; Colin Cherry; Behnam Neyshabur; Orhan Firat (ICML, 2022)

Do Current Multi-Task Optimization Methods in Deep Learning Even Help? - Derrick Xin; Behrooz Ghorbani; Justin Gilmer; Ankush Garg; Orhan Firat (NeurIPS, 2022)

Data Scaling Laws in NMT: The Effect of Noise and Architecture. - Yamini Bansal; Behrooz Ghorbani; Ankush Garg; Biao Zhang 006; Maxim Krikun; Colin Cherry; Behnam Neyshabur; Orhan Firat (CoRR, 2022)

Binarized Neural Machine Translation. - Yichi Zhang 006; Ankush Garg; Yuan Cao; Lukasz Lew; Behrooz Ghorbani; Zhiru Zhang; Orhan Firat (NeurIPS, 2023)

Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. - Dami Choi; Derrick Xin; Hamid Dadkhahi; Justin Gilmer; Ankush Garg; Orhan Firat; Chih-Kuan Yeh; Andrew M. Dai; Behrooz Ghorbani (NeurIPS, 2023)

The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation. - Patrick Fernandes; Daniel Deutsch; Mara Finkelstein; Parker Riley; André F. T. Martins; Graham Neubig; Ankush Garg; Jonathan H. Clark; Markus Freitag; Orhan Firat (WMT, 2023)

Benchmarking Neural Network Training Algorithms. - George E. Dahl; Frank Schneider 001; Zachary Nado; Naman Agarwal; Chandramouli Shama Sastry; Philipp Hennig; Sourabh Medapati; Runa Eschenhagen; Priya Kasimbeg; Daniel Suo; Juhan Bae; Justin Gilmer; et al. (CoRR, 2023)