Parameswaran Raman

22 papers A* 4A 2B 2Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent.
CoRR
Hiroki Naganuma, Shagun Gupta, Youssef Briki, Ioannis Mitliagkas, Irina Rish, Parameswaran Raman, Hao-Jun Michael Shi
2025 J jnl
Smoothing DiLoCo with Primal Averaging for Faster Training of LLMs.
CoRR
Aaron Defazio, Konstantin Mishchenko, Parameswaran Raman, Hao-Jun Michael Shi, Lin Xiao
2025 J jnl
νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints.
Trans. Mach. Learn. Res.
Thomas Pethick, Parameswaran Raman, Lenon Minorics, Mingyi Hong, Shoham Sabach, Volkan Cevher
2024 J jnl
EMC
CoRR
Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong
2024 A* conf
EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence.
ICML
Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong
2024 B conf
HLAT: High-quality Large Language Model Pre-trained on AWS Trainium.
IEEE Big Data
Haozheng Fan, Hao Zhou, Guangtai Huang, Parameswaran Raman, Xinwei Fu, Gaurav Gupta, Dhananjay Ram, Yida Wang, Jun Huan
2024 J jnl
HLAT: High-quality Large Language Model Pre-trained on AWS Trainium.
CoRR
Haozheng Fan, Hao Zhou, Guangtai Huang, Parameswaran Raman, Xinwei Fu, Gaurav Gupta, Dhananjay Ram, Yida Wang, Jun Huan
2024 A conf
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate.
AISTATS
Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher
2024 J jnl
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate.
CoRR
Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher
2024 A* conf
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent.
ICML
Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024 J jnl
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent.
CoRR
Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024 A* conf
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models.
ICML
Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman, Wooseok Ha
2024 J jnl
Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models.
CoRR
Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman, Wooseok Ha
2023 J jnl
Contractive error feedback for gradient compression.
CoRR
Bingcong Li, Shuai Zheng, Parameswaran Raman, Anshumali Shrivastava, Georgios B. Giannakis
2020 J jnl
DS-FACTO: Doubly Separable Factorization Machines.
CoRR
Parameswaran Raman, S. V. N. Vishwanathan
2019 A conf
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models.
AISTATS
Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon
2019 J jnl
Optimization on the Surface of the (Hyper)-Sphere.
CoRR
Parameswaran Raman, Jiasen Yang
2019 A* conf
Scaling Multinomial Logistic Regression via Hybrid Parallelism.
KDD
Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan
2016 J jnl
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression.
CoRR
Parameswaran Raman, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan
2014 J jnl
Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data.
CoRR
Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan
2014 — conf
Ranking via Robust Binary Classification.
NIPS
Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan
2014 B conf
Relevancy prediction of micro-blog questions in an educational setting.
EDM
Mariheida Cordova-Sanchez, Parameswaran Raman, Luo Si, Jason Fish