image:wibisono
       Andre Wibisono
UNIVERSITY OF CALIFORNIA, BERKELEY

465 Soda Hall
wibisono [at] berkeley [dot] edu

I am a fourth-year PhD student in Computer Science at UC Berkeley, advised by Michael I. Jordan. I am interested in the general statistical analysis of machine learning algorithms.

Before coming to Berkeley, I received my bachelor's degrees in mathematics and computer science in 2009 from MIT. I also received my master's degree in computer science from MIT in 2010, where I was advised by Tomaso Poggio and Lorenzo Rosasco. I received my MA degree in Statistics from Berkeley in May 2013.




PUBLICATIONS

• How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
with Jake Abernethy, Peter Bartlett, and Rafael Frongillo
To appear at Neural Information Processing System (NIPS), December 2013
• Streaming Variational Bayes
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, and Michael I. Jordan
To appear at Neural Information Processing System (NIPS), December 2013
• Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
John C. Duchi, Michael I. Jordan, Martin J. Wainwright, and Andre Wibisono
Neural Information Processing System (NIPS), December 2012
• Minimax Option Pricing Meets Black-Scholes in the Limit
Jacob Abernethy, Rafael Frongillo, and Andre Wibisono
Symposium on the Theory of Computing (STOC), May 2012

THESES

• Maximum Entropy Distributions on Graphs
Thesis for MA in Statistics, University of California, Berkeley, May 2013
• Generalization and Properties of the Neural Response
Thesis for M.Eng. in Computer Science, Massachusetts Institute of Technology, June 2010

PREPRINTS AND TECHNICAL REPORTS

• Inverses of symmetric, diagonally dominant positive matrices and applications
Christopher Hillar, Shaowei Lin, and Andre Wibisono
• Generalization and Properties of the Neural Response
Jake Bouvrie, Tomaso Poggio, Lorenzo Rosasco, Stephen Smale, and Andre Wibisono
MIT Technical Report TR-2010-051/CBCL-292, November 2010
(This is a slightly revised and expanded version of my M.Eng. thesis)
• Learning and Invariance in a Family of Hierarchical Kernels
Andre Wibisono, Jake Bouvrie, Lorenzo Rosasco, and Tomaso Poggio
MIT Technical Report TR-2010-035/CBCL-290, July 2010
• Sufficient Conditions for Uniform Stability of Regularization Algorithms
Andre Wibisono, Lorenzo Rosasco, and Tomaso Poggio
MIT Technical Report TR-2009-060/CBCL-284, December 2009