image:wibisono
      Andre Wibisono

UNIVERSITY OF CALIFORNIA, BERKELEY

wibisono [at] berkeley [dot] edu

I received my PhD in computer science from UC Berkeley in 2016, advised by Michael Jordan, and my MA in Statistics in 2013.

I received my bachelor's degrees in mathematics and computer science from MIT in 2009, and my MEng in computer science in 2010, advised by Tomaso Poggio.


RESEARCH

A variational perspective on accelerated methods in optimization
Andre Wibisono, Ashia Wilson, and Michael Jordan
arXiv:1603.04245, 2016
Optimal rates for zero-order convex optimization: the power of two function evaluations
John Duchi, Michael Jordan, Martin Wainwright, and Andre Wibisono
IEEE Transactions on Information Theory, 61(5): 2788--2806, May 2015
A Hadamard-type lower bound for symmetric diagonally dominant positive matrices
Christopher Hillar and Andre Wibisono
Linear Algebra and Applications, 472: 135--141, 2015
Convexity of reweighted Kikuchi approximation
Po-Ling Loh and Andre Wibisono
NIPS (Neural Information Processing System) 2014
How to hedge an option against an adversary: Black-Scholes pricing is minimax optimal
Jake Abernethy, Peter Bartlett, Rafael Frongillo, and Andre Wibisono
NIPS (Neural Information Processing System) 2013
Streaming variational Bayes
Tamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia Wilson, and Michael Jordan
NIPS (Neural Information Processing System) 2013
Maximum entropy distributions on graphs
Christopher Hillar and Andre Wibisono
arXiv:1301.3321, 2013
Inverses of symmetric, diagonally dominant positive matrices and applications
Christopher Hillar, Shaowei Lin, and Andre Wibisono
arXiv:1203.6812, 2013
Finite sample convergence rates of zero-order stochastic optimization methods
John Duchi, Michael Jordan, Martin Wainwright, and Andre Wibisono
NIPS (Neural Information Processing System) 2012
Minimax option pricing meets Black-Scholes in the limit
Jacob Abernethy, Rafael Frongillo, and Andre Wibisono
STOC (Symposium on the Theory of Computing) 2012

Variational and Dynamical Perspectives on Learning and Optimization
PhD in Computer Science, University of California, Berkeley, May 2016
Maximum Entropy Distributions on Graphs
MA in Statistics, University of California, Berkeley, May 2013
Generalization and Properties of the Neural Response
MEng in Computer Science, Massachusetts Institute of Technology, June 2010