Parameswaran Raman

According to our database, Parameswaran Raman authored at least 15 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Jun Huan

CoRR, 2024

EMC²: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence.

Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong

CoRR, 2024

EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence.

Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman, Soumajyoti Sarkar, Mingyi Hong

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent.

Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models.

Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman, Wooseok Ha

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate.

Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Contractive error feedback for gradient compression.

Bingcong Li, Shuai Zheng, Parameswaran Raman, Anshumali Shrivastava, Georgios B. Giannakis

CoRR, 2023

2020

DS-FACTO: Doubly Separable Factorization Machines.

Parameswaran Raman, S. V. N. Vishwanathan

CoRR, 2020

2019

Optimization on the Surface of the (Hyper)-Sphere.

Parameswaran Raman, Jiasen Yang

CoRR, 2019

Scaling Multinomial Logistic Regression via Hybrid Parallelism.

Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models.

Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2016

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

2014

Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

CoRR, 2014

Ranking via Robust Binary Classification.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Relevancy prediction of micro-blog questions in an educational setting.

Mariheida Cordova-Sanchez, Parameswaran Raman, Luo Si, Jason Fish

Proceedings of the 7th International Conference on Educational Data Mining, 2014