Balasubramanian, Krishna

18 publications

NeurIPS 2025 Dense Associative Memory with Epanechnikov Energy Benjamin Hoover, Zhaoyang Shi, Krishna Balasubramanian, Dmitry Krotov, Parikshit Ram

ICLRW 2025 Dense Associative Memory with Epanechnikov Energy Benjamin Hoover, Krishna Balasubramanian, Dmitry Krotov, Parikshit Ram

ICLR 2025 Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent Sayan Banerjee, Krishna Balasubramanian, Promit Ghosal

TMLR 2025 In-Context Learning for Mixture of Linear Regression: Existence, Generalization and Training Dynamics Yanhao Jin, Krishna Balasubramanian, Lifeng Lai

UAI 2025 Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik

NeurIPS 2025 Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions Jhanvi Garg, Krishna Balasubramanian, Quan Zhou

NeurIPS 2025 Riemannian Proximal Sampler for High-Accuracy Sampling on Manifolds Yunrui Guan, Krishna Balasubramanian, Shiqian Ma

ICLR 2025 Transformers Handle Endogeneity in In-Context Linear Regression Haodong Liang, Krishna Balasubramanian, Lifeng Lai

AISTATS 2024 Adaptive and Non-Adaptive Minimax Rates for Weighted Laplacian-Eigenmap Based Nonparametric Regression Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik

TMLR 2024 From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression Xuxing Chen, Krishna Balasubramanian, Promit Ghosal, Bhavya Kumar Agrawalla

ICML 2023 Decentralized Stochastic Bilevel Optimization with Improved Per-Iteration Complexity Xuxing Chen, Minhui Huang, Shiqian Ma, Krishna Balasubramanian

ICML 2023 Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim

COLT 2023 Improved Discretization Analysis for Underdamped Langevin Monte Carlo Shunshi Zhang, Sinho Chewi, Mufan Li, Krishna Balasubramanian, Murat A. Erdogdu

COLT 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

UAI 2022 High-Probability Bounds for Robust Stochastic Frank-Wolfe Algorithm Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee

COLT 2022 Mirror Descent Strikes Again: Optimal Stochastic Convex Optimization Under Infinite Noise Variance Nuri Mert Vural, Lu Yu, Krishna Balasubramanian, Stanislav Volgushev, Murat A Erdogdu

COLT 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

ICML 2020 Fractal Gaussian Networks: A Sparse Random Graph Model Based on Gaussian Multiplicative Chaos Subhroshekhar Ghosh, Krishna Balasubramanian, Xiaochuan Yang