Sayan Mukherjee

According to our database, Sayan Mukherjee authored at least 71 papers between 1995 and 2024.

Collaborative distances:

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

2024

Representing fields without correspondences: the lifted Euler characteristic transform.

Henry Kirveslahti, Sayan Mukherjee

J. Appl. Comput. Topol., March, 2024

2023

Ergodic theorems for dynamic imprecise probability kinematics.

Michele Caprio, Sayan Mukherjee

Int. J. Approx. Reason., 2023

Global Optimality of Elman-type RNN in the Mean-Field Regime.

Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee

CoRR, 2023

Concentration Inequalities and Optimal Number of Layers for Stochastic Deep Neural Networks.

Michele Caprio, Sayan Mukherjee

IEEE Access, 2023

Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression.

Youngsoo Baek, Samuel Berchuck, Sayan Mukherjee

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Global optimality of Elman-type RNNs in the mean-field regime.

Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee

Proceedings of the International Conference on Machine Learning, 2023

2022

Learning Subspaces of Different Dimensions.

Brian St. Thomas, Kisung You, Lizhen Lin, Lek-Heng Lim, Sayan Mukherjee

J. Comput. Graph. Stat., January, 2022

A topological data analytic approach for discovering biophysical signatures in protein dynamics.

Wai-Shing Tang, Gabriel Monteiro da Silva, Henry Kirveslahti, Erin Skeens, Bibo Feng, Timothy Sudijono, Kevin K. Yang, Sayan Mukherjee, Brenda M. Rubenstein, Lorin Crawford

PLoS Comput. Biol., 2022

The accuracy of absolute differential abundance analysis from relative count data.

Kimberly Roche, Sayan Mukherjee

PLoS Comput. Biol., 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

J. Mach. Learn. Res., 2022

A Sheaf-Theoretic Construction of Shape Space.

Shreya Arya, Justin Curry, Sayan Mukherjee

CoRR, 2022

2021

Measuring and mitigating PCR bias in microbiota datasets.

Justin D. Silverman, Rachael J. Bloom, Sharon Jiang, Heather K. Durand, Eric Dallow, Sayan Mukherjee, Lawrence A. David

PLoS Comput. Biol., 2021

Subspace Clustering through Sub-Clusters.

Weiwei Li, Jan Hannig, Sayan Mukherjee

J. Mach. Learn. Res., 2021

The Geometry of Synchronization Problems and Learning Group Actions.

Tingran Gao, Jacek Brodzki, Sayan Mukherjee

Discret. Comput. Geom., 2021

Accelerating Markov Random Field Inference with Uncertainty Quantification.

Ramin Bashizade, Xiangyu Zhang, Sayan Mukherjee, Alvin R. Lebeck

CoRR, 2021

Towards Explainable Convolutional Features for Music Audio Modeling.

Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier, Sayan Mukherjee, Vahid Tarokh

CoRR, 2021

A Bayesian hierarchical model to estimate DNA methylation conservation in colorectal tumors.

Kevin A. Murgas, Yanlin Ma, Lidea K. Shahidi, Sayan Mukherjee, Andrew S. Allen, Darryl Shibata, Marc D. Ryser

Bioinform., 2021

Statistical robustness of Markov chain Monte Carlo accelerators.

Xiangyu Zhang, Ramin Bashizade, Yicheng Wang, Sayan Mukherjee, Alvin R. Lebeck

Proceedings of the ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021

2020

At the Intersection of Deep Sequential Model Framework and State-space Model Framework: Study on Option Pricing.

Ziyang Ding, Sayan Mukherjee

CoRR, 2020

Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series.

Anna K. Yanchenko, Sayan Mukherjee

CoRR, 2020

Beyond Application End-Point Results: Quantifying Statistical Robustness of MCMC Accelerators.

Xiangyu Zhang, Ramin Bashizade, Yicheng Wang, Cheng Lyu, Sayan Mukherjee, Alvin R. Lebeck

CoRR, 2020

2019

A Case for Quantifying Statistical Robustness of Specialized Probabilistic AI Accelerators.

Xiangyu Zhang, Sayan Mukherjee, Alvin R. Lebeck

CoRR, 2019

Adaptive particle-based approximations of the Gibbs posterior for inverse problems.

Zilong Zou, Sayan Mukherjee, Harbir Antil, Wilkins Aquino

CoRR, 2019

2018

Multiple testing with persistent homology.

Mikael Vejdemo-Johansson, Sayan Mukherjee

CoRR, 2018

Learning Integral Representations of Gaussian Processes.

Zilong Tan, Sayan Mukherjee

CoRR, 2018

Scalable Algorithms for Learning High-Dimensional Linear Mixed Models.

Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2017

Adaptive Randomized Dimension Reduction on Massive Data.

Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee, Barbara E. Engelhardt

J. Mach. Learn. Res., 2017

Classical Music Composition Using State Space Models.

Anna K. Yanchenko, Sayan Mukherjee

CoRR, 2017

Efficient Learning of Graded Membership Models.

Zilong Tan, Sayan Mukherjee

CoRR, 2017

Partitioned Tensor Factorizations for Learning Mixed Membership Models.

Zilong Tan, Sayan Mukherjee

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Random walks on simplicial complexes and harmonics.

Sayan Mukherjee, John Steenbergen

Random Struct. Algorithms, 2016

Bayesian group factor analysis with structured sparsity.

Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E. Engelhardt

J. Mach. Learn. Res., 2016

Fast moment estimation for generalized latent Dirichlet models.

Shiwen Zhao, Barbara E. Engelhardt, Sayan Mukherjee, David B. Dunson

CoRR, 2016

2015

The Information Geometry of Mirror Descent.

Garvesh Raskutti, Sayan Mukherjee

IEEE Trans. Inf. Theory, 2015

Cumulon: Matrix-Based Data Analytics in the Cloud with Spot Instances.

Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, Jun Yang

Proc. VLDB Endow., 2015

Contour trees of uncertain terrains.

Wuzhou Zhang, Pankaj K. Agarwal, Sayan Mukherjee

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015

2014

Cumulon: Cloud-Based Statistical Analysis from Users Perspective.

Botong Huang, Nicholas W. D. Jarrett, Shivnath Babu, Sayan Mukherjee, Jun Yang

IEEE Data Eng. Bull., 2014

Fréchet Means for Distributions of Persistence Diagrams.

Katharine Turner, Yuriy Mileyko, Sayan Mukherjee, John Harer

Discret. Comput. Geom., 2014

A Cheeger-type inequality on simplicial complexes.

John Steenbergen, Caroline J. Klivans, Sayan Mukherjee

Adv. Appl. Math., 2014

2013

A comparative study of covariance selection models for the inference of gene regulatory networks.

Patrizia F. Stifanelli, Teresa Maria Creanza, Roberto Anglani, Vania C. Liuzzi, Sayan Mukherjee, Francesco P. Schena, Nicola Ancona

J. Biomed. Informatics, 2013

Probabilistic Fréchet Means and Statistics on Vineyards.

Elizabeth Munch, Paul Bendich, Katharine Turner, Sayan Mukherjee, Jonathan Mattingly, John Harer

CoRR, 2013

Genome-wide identification and predictive modeling of tissue-specific alternative polyadenylation.

Dina Hafez, Ting Ni, Sayan Mukherjee, Jun Zhu, Uwe Ohler

Bioinform., 2013

2012

Local homology transfer and stratification learning.

Paul Bendich, Bei Wang, Sayan Mukherjee

Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012

2011

Estimating variable structure and dependence in multitask learning via gradients.

Justin Guinney, Qiang Wu, Sayan Mukherjee

Mach. Learn., 2011

2010

Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence.

Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee

J. Mach. Learn. Res., 2010

Supervised Dimension Reduction Using Bayesian Mixture Modeling.

Kai Mao, Feng Liang, Sayan Mukherjee

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

On the reproducibility of results of pathway analysis in genome-wide expression studies of colorectal cancers.

Rosalia Maglietta, Angela Distaso, Ada Piepoli, Orazio Palumbo, Massimo Carella, Annarita D'Addabbo, Sayan Mukherjee, Nicola Ancona

J. Biomed. Informatics, 2010

Stratification Learning through Homology Inference.

Paul Bendich, Sayan Mukherjee, Bei Wang

Proceedings of the Manifold Learning and Its Applications, 2010

2009

Comparative study of gene set enrichment methods.

Luca Abatangelo, Rosalia Maglietta, Angela Distaso, Annarita D'Addabbo, Teresa Maria Creanza, Sayan Mukherjee, Nicola Ancona

BMC Bioinform., 2009

2008

Modeling Cancer Progression via Pathway Dependencies.

Elena J. Edelman, Justin Guinney, Jen-Tsan A. Chi, Phillip G. Febbo, Sayan Mukherjee

PLoS Comput. Biol., 2008

Localized Sliced Inverse Regression.

Qiang Wu, Sayan Mukherjee, Feng Liang

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Statistical Assessment of MSigDB Gene Sets in Colon Cancer.

Angela Distaso, Luca Abatangelo, Rosalia Maglietta, Teresa Maria Creanza, Ada Piepoli, Massimo Carella, Annarita D'Addabbo, Sayan Mukherjee, Nicola Ancona

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

2007

Characterizing the Function Space for Bayesian Kernel Models.

Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert

J. Mach. Learn. Res., 2007

Genomic sweeping for hypermethylated genes.

Liang Goh, Susan K. Murphy, Sayan Mukherjee, Terrence S. Furey

Bioinform., 2007

Decision Fusion of Circulating Markers for Breast Cancer Detection in Premenopausal Women.

Jonathan L. Jesneck, Sayan Mukherjee, Loren W. Nolte, Anna E. Lokshin, Jeffrey R. Marks, Joseph Y. Lo

Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007

2006

Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation.

Zhong Wang, Huntington F. Willard, Sayan Mukherjee, Terrence S. Furey

PLoS Comput. Biol., 2006

Learning Coordinate Covariances via Gradients.

Sayan Mukherjee, Ding-Xuan Zhou

J. Mach. Learn. Res., 2006

Estimation of Gradients and Coordinate Covariation in Classification.

Sayan Mukherjee, Qiang Wu

J. Mach. Learn. Res., 2006

Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization.

Sayan Mukherjee, Partha Niyogi, Tomaso A. Poggio, Ryan M. Rifkin

Adv. Comput. Math., 2006

Analysis of sample set enrichment scores: assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles.

Elena J. Edelman, Alessandro Porrello, Justin Guinney, Bala Balakumaran, Andrea Bild, Phillip G. Febbo, Sayan Mukherjee

Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

2005

Gene Selection via a Spectral Approach.

Lior Wolf, Amnon Shashua, Sayan Mukherjee

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005

Permutation Tests for Classification.

Polina Golland, Feng Liang, Sayan Mukherjee, Dmitry Panchenko

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2003

An Analytical Method for Multiclass Molecular Cancer Classification.

Ryan M. Rifkin, Sayan Mukherjee, Pablo Tamayo, Sridhar Ramaswamy, Chen-Hsiang Yeang, Michael Angelo, Michael Reich, Tomaso A. Poggio, Eric S. Lander, Todd R. Golub, Jill P. Mesirov

SIAM Rev., 2003

Estimating Dataset Size Requirements for Classifying DNA Microarray Data.

Sayan Mukherjee, Pablo Tamayo, Simon Rogers, Ryan M. Rifkin, Anna Engle, Colin Campbell, Todd R. Golub, Jill P. Mesirov

J. Comput. Biol., 2003

2002

Choosing Multiple Parameters for Support Vector Machines.

Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee

Mach. Learn., 2002

Predicting Signal Peptides with Support Vector Machines.

Neelanjan Mukherjee, Sayan Mukherjee

Proceedings of the Pattern Recognition with Support Vector Machines, 2002

2001

Molecular classification of multiple tumor types.

Chen-Hsiang Yeang, Sridhar Ramaswamy, Pablo Tamayo, Sayan Mukherjee, Ryan M. Rifkin, Michael Angelo, Michael Reich, Eric S. Lander, Jill P. Mesirov, Todd R. Golub

Proceedings of the Ninth International Conference on Intelligent Systems for Molecular Biology, 2001

Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images.

Bernd Heisele, Thomas Serre, Sayan Mukherjee, Tomaso A. Poggio

Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 2001

2000

Feature Selection for SVMs.

Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso A. Poggio, Vladimir Vapnik

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1996

Automatic generation of RBF networks using wavelets.

Shayan Mukherjee, Shree K. Nayar

Pattern Recognit., 1996

1995

Automatic Generation of GRBF Networks for Visual Learning.

Shayan Mukherjee, Shree K. Nayar

Proceedings of the Procedings of the Fifth International Conference on Computer Vision (ICCV 95), 1995