Advait Gadhikar

14 papers A* 1Misc 1Journal 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	HAM: A Hyperbolic Step to Regulate Implicit Bias. CoRR Tom Jacobs, Advait Gadhikar, Celia Rubio-Madrigal, Rebekka Burkholz
2025	J	`jnl`	OptRot: Mitigating Weight Outliers via Data-Free Rotations for Post-Training Quantization. CoRR Advait Gadhikar, Riccardo Grazzi, James Hensman
2025	J	`jnl`	Pay Attention to Small Weights. CoRR Chao Zhou, Tom Jacobs, Advait Gadhikar, Rebekka Burkholz
2025	J	`jnl`	Sign-In to the Lottery: Reparameterizing Sparse Training From Scratch. CoRR Advait Gadhikar, Tom Jacobs, Chao Zhou, Rebekka Burkholz
2024	J	`jnl`	Attention Is All You Need For Mixture-of-Depths Routing. CoRR Advait Gadhikar, Souptik Kumar Majumdar, Niclas Popp, Piyapat Saranrittichai, Martin Rapp, Lukas Schott
2024	J	`jnl`	Cyclic Sparse Training: Is it Enough? CoRR Advait Gadhikar, Sree Harsha Nelaturu, Rebekka Burkholz
2024	J	`jnl`	Masks, Signs, And Learning Rate Rewinding. CoRR Advait Gadhikar, Rebekka Burkholz
2022	J	`jnl`	Dynamical Isometry for Residual Networks. CoRR Advait Gadhikar, Rebekka Burkholz
2022	J	`jnl`	How Erdös and Rényi Win the Lottery. CoRR Advait Gadhikar, Sohom Mukherjee, Rebekka Burkholz
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
2021	Misc	`conf`	Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning. ICASSP Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar
2021	J	`jnl`	Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning. CoRR Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar
2021	A*	`conf`	Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. NeurIPS Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi
2021	J	`jnl`	Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. CoRR Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi