activity
20162019
most citedDynamic Energy Management

16 citations · 16 across the 4 of their papers we have counts for

collaborators

7 papers

stat.ML2019

Seasonally-Adjusted Auto-Regression of Vector Time Series

Enzo Busseti

We present a simple algorithm to forecast vector time series, that is robust against missing data, in both training and inference. It models seasonal annual, weekly, and daily base…

math.OC2019

Differentiating Through a Cone Program

Akshay Agrawal, Shane Barratt, Stephen Boyd +2

We consider the problem of efficiently computing the derivative of the solution map of a convex cone program, when it exists. We do this by implicitly differentiating the residual…

math.OC2019

Derivative of a Conic Problem with a Unique Solution

Enzo Busseti

We view a conic optimization problem that has a unique solution as a map from its data to its solution. If sufficient regularity conditions hold at a solution point, namely that th…

q-fin.PR2019

Risk and Return models for Equity Markets and Implied Equity Risk Premium

Enzo Busseti

Equity risk premium is a central component of every risk and return model in finance and a key input to estimate costs of equity and capital in both corporate finance and valuation…

math.OC201916 cited

Dynamic Energy Management

Nicholas Moehle, Enzo Busseti, Stephen Boyd +1

We present a unified method, based on convex optimization, for managing the power produced and consumed by a network of devices over time. We start with the simple setting of optim…

math.OC2018

Solution Refinement at Regular Points of Conic Problems

E. Busseti, W. Moursi, S. Boyd

Most numerical methods for conic problems use the homogenous primal-dual embedding, which yields a primal-dual solution or a certificate establishing primal or dual infeasibility.…