Krishna Balasubramanian

According to our database, Krishna Balasubramanian authored at least 17 papers between 2008 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2025

Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps.

Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Transformers Handle Endogeneity in In-Context Linear Regression.

Haodong Liang, Krishna Balasubramanian, Lifeng Lai

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent.

Sayan Banerjee, Krishna Balasubramanian, Promit Ghosal

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Online Covariance Estimation in Nonsmooth Stochastic Approximation.

Liwei Jiang, Abhishek Roy, Krishna Balasubramanian, Damek Davis, Dmitriy Drusvyatskiy, Sen Na

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression.

Xuxing Chen, Krishna Balasubramanian, Promit Ghosal, Bhavya Agrawalla

Trans. Mach. Learn. Res., 2024

Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression.

Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik

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

2023

Winding Through: Crowd Navigation via Topological Invariance.

Christoforos I. Mavrogiannis, Krishna Balasubramanian, Sriyash Poddar, Anush Gandra, Siddhartha S. Srinivasa

IEEE Robotics Autom. Lett., 2023

Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space.

Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim

Proceedings of the International Conference on Machine Learning, 2023

Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity.

Xuxing Chen, Minhui Huang, Shiqian Ma, Krishna Balasubramanian

Proceedings of the International Conference on Machine Learning, 2023

Improved Discretization Analysis for Underdamped Langevin Monte Carlo.

Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality.

Alireza Mousavi Hosseini, Tyler K. Farghly, Ye He, Krishna Balasubramanian, Murat A. Erdogdu

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

High-probability bounds for robust stochastic Frank-Wolfe algorithm.

Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo.

Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Topology-Informed Model Predictive Control for Anticipatory Collision Avoidance on a Ballbot.

Christoforos I. Mavrogiannis, Krishna Balasubramanian, Sriyash Poddar, Anush Gandra, Siddhartha S. Srinivasa

CoRR, 2021

2020

High Tc Superconducting Tunnel Junctions For Cryogenic Temperature Measurement.

Krishna Balasubramanian

Proceedings of the 2020 IEEE Sensors, Rotterdam, The Netherlands, October 25-28, 2020, 2020

2019

Low-Rank Principal Eigenmatrix Analysis.

Krishna Balasubramanian, Elynn Y. Chen, Jianqing Fan, Xiang Wu

CoRR, 2019

2008

Inferring functional linkage from residue level co-evolution information.

Roger A. Craig, Keyur Malaviya, Krishna Balasubramanian, Li Liao

Proceedings of the International Conference on Bioinformatics & Computational Biology, 2008