62 citations · 268 across the 38 of their papers we have counts for
6 papers · 1 filter
At the Intersection of Deep Sequential Model Framework and State-space Model Framework: Study on Option Pricing
Ziyang Ding, Sayan Mukherjee
Inference and forecast problems of the nonlinear dynamical system have arisen in a variety of contexts. Reservoir computing and deep sequential models, on the one hand, have demons…
Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series
Anna K. Yanchenko, Sayan Mukherjee
Time series with long-term structure arise in a variety of contexts and capturing this temporal structure is a critical challenge in time series analysis for both inference and for…
Subspace Clustering through Sub-Clusters
Weiwei Li, Jan Hannig, Sayan Mukherjee
The problem of dimension reduction is of increasing importance in modern data analysis. In this paper, we consider modeling the collection of points in a high dimensional space as…
Learning Integral Representations of Gaussian Processes
Zilong Tan, Sayan Mukherjee
We propose a representation of Gaussian processes (GPs) based on powers of the integral operator defined by a kernel function, we call these stochastic processes integral Gaussian…
Adaptive Randomized Dimension Reduction on Massive Data
Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee +1
The scalability of statistical estimators is of increasing importance in modern applications. One approach to implementing scalable algorithms is to compress data into a low dimens…
The Information Geometry of Mirror Descent
Garvesh Raskutti, Sayan Mukherjee
Information geometry applies concepts in differential geometry to probability and statistics and is especially useful for parameter estimation in exponential families where paramet…