Publications (7)
Eigen-Stratified Models
Jonathan Tuck, Stephen Boyd
Stratified models depend in an arbitrary way on a selected categorical feature that takes values, and depend linearly on the other features. Laplacian regularization with r…
Portfolio Construction Using Stratified Models
Jonathan Tuck, Shane Barratt, Stephen Boyd
In this paper we develop models of asset return mean and covariance that depend on some observable market conditions, and use these to construct a trading policy that depends on th…
Convex Optimization Over Risk-Neutral Probabilities
Shane Barratt, Jonathan Tuck, Stephen Boyd
We consider a collection of derivatives that depend on the price of an underlying asset at expiration or maturity. The absence of arbitrage is equivalent to the existence of a risk…
Distributed Majorization-Minimization for Laplacian Regularized Problems
Jonathan Tuck, David Hallac, Stephen Boyd
We consider the problem of minimizing a block separable convex function (possibly nondifferentiable, and including constraints) plus Laplacian regularization, a problem that arises…
Fitting Laplacian Regularized Stratified Gaussian Models
Jonathan Tuck, Stephen Boyd
We consider the problem of jointly estimating multiple related zero-mean Gaussian distributions from data. We propose to jointly estimate these covariance matrices using Laplacian…
Polyphase Waveform Design for MIMO Radar Space Time Adaptive Processing
Bo Tang, Jonathan Tuck, Peter Stoica
We consider the design of polyphase waveforms for ground moving target detection with airborne multiple-input-multiple-output (MIMO) radar. Due to the constant-modulus and finite-a…
A Distributed Method for Fitting Laplacian Regularized Stratified Models
Jonathan Tuck, Shane Barratt, Stephen Boyd
Stratified models are models that depend in an arbitrary way on a set of selected categorical features, and depend linearly on the other features. In a basic and traditional formul…