Ramchandran, Kannan

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Yin, D., Chen, Y., Ramchandran, K., & Bartlett, P. (2018) · arXiv

Stochastic Gradient Optimization TechniquesPrivacy-Preserving Technologies in Data

Cited by 1,130

Speeding Up Distributed Machine Learning Using Codes

Lee, K., Lam, M., Pedarsani, R., Papailiopoulos, D., & Ramchandran, K. (2018) · IEEE Transactions on Information Theory

Advanced Data Storage TechnologiesStochastic Gradient Optimization Techniques

Cited by 829

Why Do Multi-Agent LLM Systems Fail?

Cemri, M., Pan, M. Z., Yang, S., Agrawal, L. A., Chopra, B., Tiwari, R., Keutzer, K., Parameswaran, A., Klein, D., Ramchandran, K., et al. (2025) · arXiv

Multi-Agent Systems and NegotiationNatural Language Processing Techniques

Cited by 630

Fundamental limits of DNA storage systems

Heckel, R., Shomorony, I., Ramchandran, K., & Tse, D. N. C. (2017) · 2017 IEEE International Symposium on Information Theory (ISIT)

DNA and Biological ComputingAlgorithms and Data Compression

Cited by 123

Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment

Wu, T., Zhu, B., Zhang, R., Wen, Z., Ramchandran, K., & Jiao, J. (2023) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 4

Looped Transformers for Length Generalization

Fan, Y., Du, Y., Ramchandran, K., & Lee, K. (2024) · arXiv

semigroups and automata theoryComputability, Logic, AI Algorithms

Cited by 0

EmbedLLM: Learning Compact Representations of Large Language Models

Zhuang, R., Wu, T., Wen, Z., Li, A., Jiao, J., & Ramchandran, K. (2024) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 0