Relevancy prediction of micro-blog questions in an educational setting. - Mariheida Cordova-Sanchez; Parameswaran Raman; Luo Si; Jason Fish (EDM, 2014)

Ranking via Robust Binary Classification. - Hyokun Yun; Parameswaran Raman; S. V. N. Vishwanathan (NIPS, 2014)

Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data. - Hyokun Yun; Parameswaran Raman; S. V. N. Vishwanathan (CoRR, 2014)

DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression. - Parameswaran Raman; Shin Matsushima; Xinhua Zhang; Hyokun Yun; S. V. N. Vishwanathan (CoRR, 2016)

Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. - Jiong Zhang; Parameswaran Raman; Shihao Ji 001; Hsiang-Fu Yu; S. V. N. Vishwanathan; Inderjit S. Dhillon (AISTATS, 2019)

Scaling Multinomial Logistic Regression via Hybrid Parallelism. - Parameswaran Raman; Sriram Srinivasan 004; Shin Matsushima; Xinhua Zhang; Hyokun Yun; S. V. N. Vishwanathan (KDD, 2019)

Optimization on the Surface of the (Hyper)-Sphere. - Parameswaran Raman; Jiasen Yang (CoRR, 2019)

DS-FACTO: Doubly Separable Factorization Machines. - Parameswaran Raman; S. V. N. Vishwanathan (CoRR, 2020)

Contractive error feedback for gradient compression. - Bingcong Li; Shuai Zheng; Parameswaran Raman; Anshumali Shrivastava; Georgios B. Giannakis (CoRR, 2023)

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate. - Ruichen Jiang; Parameswaran Raman; Shoham Sabach; Aryan Mokhtari; Mingyi Hong 001; Volkan Cevher (AISTATS, 2024)

HLAT: High-quality Large Language Model Pre-trained on AWS Trainium. - Haozheng Fan; Hao Zhou; Guangtai Huang; Parameswaran Raman; Xinwei Fu; Gaurav Gupta; Dhananjay Ram; Yida Wang 003; Jun Huan (IEEE Big Data, 2024)

Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models. - Tanmay Gautam; Youngsuk Park; Hao Zhou; Parameswaran Raman; Wooseok Ha (ICML, 2024)

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. - Kaan Ozkara; Can Karakus; Parameswaran Raman; Mingyi Hong 001; Shoham Sabach; Branislav Kveton; Volkan Cevher (ICML, 2024)

EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. - Chung-Yiu Yau; Hoi-To Wai; Parameswaran Raman; Soumajyoti Sarkar; Mingyi Hong 001 (ICML, 2024)

EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. - Chung-Yiu Yau; Hoi-To Wai; Parameswaran Raman; Soumajyoti Sarkar; Mingyi Hong 001 (CoRR, 2024)

νSAM: Memory-Efficient Sharpness-Aware Minimization via Nuclear Norm Constraints. - Thomas Pethick; Parameswaran Raman; Lenon Minorics; Mingyi Hong 001; Shoham Sabach; Volkan Cevher (Trans. Mach. Learn. Res., 2025)