Mukherjee, Sayan

28 publications

TMLR 2025 Local Differential Privacy-Preserving Spectral Clustering for General Graphs Sayan Mukherjee, Vorapong Suppakitpaisarn

NeurIPS 2023 Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression Youngsoo Baek, Samuel Berchuck, Sayan Mukherjee

ICML 2023 Global Optimality of Elman-Type RNNs in the Mean-Field Regime Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee

JMLR 2022 Bayesian Multinomial Logistic Normal Models Through Marginally Latent Matrix-T Processes Justin D. Silverman, Kimberly Roche, Zachary C. Holmes, Lawrence A. David, Sayan Mukherjee

COLT 2022 Tight Query Complexity Bounds for Learning Graph Partitions Xizhi Liu, Sayan Mukherjee

JMLR 2021 Subspace Clustering Through Sub-Clusters Weiwei Li, Jan Hannig, Sayan Mukherjee

NeurIPSW 2020 Multiple Hypothesis Testing with Persistent Homology Mikael Vejdemo-Johansson, Sayan Mukherjee

UAI 2018 Scalable Algorithms for Learning High-Dimensional Linear Mixed Models Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee

JMLR 2017 Adaptive Randomized Dimension Reduction on Massive Data Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee, Barbara E Engelhardt

ICML 2017 Partitioned Tensor Factorizations for Learning Mixed Membership Models Zilong Tan, Sayan Mukherjee

JMLR 2016 Bayesian Group Factor Analysis with Structured Sparsity Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E Engelhardt

MLJ 2011 Estimating Variable Structure and Dependence in Multitask Learning via Gradients Justin Guinney, Qiang Wu, Sayan Mukherjee

JMLR 2010 Learning Gradients: Predictive Models That Infer Geometry and Statistical Dependence Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee

AISTATS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling Kai Mao, Feng Liang, Sayan Mukherjee

NeurIPS 2008 Localized Sliced Inverse Regression Qiang Wu, Sayan Mukherjee, Feng Liang

JMLR 2007 Characterizing the Function Space for Bayesian Kernel Models Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert

JMLR 2006 Estimation of Gradients and Coordinate Covariation in Classification Sayan Mukherjee, Qiang Wu

JMLR 2006 Learning Coordinate Covariances via Gradients Sayan Mukherjee, Ding-Xuan Zhou

CVPR 2005 Gene Selection via a Spectral Approach Lior Wolf, Amnon Shashua, Sayan Mukherjee

CVPRW 2005 Gene Selection via a Spectral Approach Lior Wolf, Amnon Shashua, Sayan Mukherjee

COLT 2005 Permutation Tests for Classification Polina Golland, Feng Liang, Sayan Mukherjee, Dmitry Panchenko

MLJ 2002 Choosing Multiple Parameters for Support Vector Machines Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee

COLT 2001 Bounds on Sample Size for Policy Evaluation in Markov Environments Leonid Peshkin, Sayan Mukherjee

CVPR 2001 Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images Bernd Heisele, Thomas Serre, Sayan Mukherjee, Tomaso A. Poggio

NeurIPS 2001 The Fidelity of Local Ordinal Encoding Javid Sadr, Sayan Mukherjee, Keith Thoresz, Pawan Sinha

NeurIPS 2000 Feature Selection for SVMs Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik

ALT 2000 On the Noise Model of Support Vector Machines Regression Massimiliano Pontil, Sayan Mukherjee, Federico Girosi

NeurIPS 1999 Support Vector Method for Multivariate Density Estimation Vladimir Vapnik, Sayan Mukherjee