Luis Rademacher's Home Page

Luis Rademacher

Office:
Dreese Labs 495
2015 Neil Avenue
Columbus, OH 43210

Phone: (614) 292-3083

E-mail :

lrademac [at] cse [dot] ohio-state [dot] edu

I am an Assistant Professor at the School of Computer Science and Engineering, Ohio State University. I am a member of the Theory and Algorithms group. I am a member of the advisory committee of The Steam Factory.

CV (PDF) (Jan 2011)

News

February-March 2012: Visiting Microsoft Research India in Bangalore.
March-May 2011: Visiting the Isaac Newton Institute for Mathematical Sciences, Cambrigde, UK.
January 2011: Teaching "Randomized algorithms and matrix decompositions" for the VI Summer School in Discrete Mathematics at the Institute of Complex Systems, Valparaíso, Chile.

Selected presentations

Simplicial polytopes that maximize the isotropic constant are highly symmetric.
AMS Sectional Meeting, Akron OH, 2012: PDF
Randomized algorithms for the approximation of matrices
FoCM 2011, Learning theory workshop: PDF
IMA, High dimensional phenomena: PDF

Advisees

James Voss (PhD, jointly advised with Mikhail Belkin)
Joseph Anderson (PhD)
Abhisek Kundu (MS, now a PhD student at RPI)
Jie Cui (MS)

Publications (PDF files)

Efficient learning of simplices. (Joseph Anderson, Navin Goyal)
COLT 2013.
Blind signal separation in the presence of Gaussian noise. (Mikhail Belkin, James Voss)
COLT 2013.
Lower bounds for the smoothed number of Pareto optima. (Navin Goyal)
FSTTCS 2012. Arxiv.
Lower bounds on partitions and applications to query complexity. (Navin Goyal, Santosh Vempala)
To appear in Combinatorics, Probability and Computing.
Efficient volume sampling for row/column subset selection. (Amit Deshpande)
FOCS 2010.
On the Monotonicity of the Expected Volume of a Random Simplex.
Mathematika. Arxiv. Presentation at Oberwolfach: PPTX, PDF.
Computational experiments for the 3-dimensional case.
Optimization of a Convex Program with a Polynomial Perturbation. (Ravi Kannan)
OR Letters.
Learning Convex Bodies is Hard. (Navin Goyal)
COLT 2009.
Expanders via Random Spanning Trees. (Navin Goyal, Santosh Vempala)
SODA 2009.
Minimal Partitioning into Product Sets. (Xuancheng Shao) In preparation.
Approximating the Centroid is Hard. PDF presentation.
SOCG 2007.
Dispersion of Mass and the Complexity of Geometric Problems.
PhD thesis, Deparment of Mathematics, MIT, 2007.
Dispersion of Mass and the Complexity of Randomized Geometric Algorithms. (Santosh Vempala)
Advances in Mathematics and FOCS 2006.
PDF presentation of the volume lower bound.
Computing Equilibrium Prices in Exchange Economies with Tax Distortions. (Bruno Codenotti, Kasturi Varadarajan)
ICALP 2006.
Matrix Approximation and Projective Clustering via Volume Sampling. (Amit Deshpande, Santosh Vempala, Grant Wang)
Theory of Computing and SODA 2006. Short PDF presentation.
Testing geometric convexity. (Santosh Vempala)
FSTTCS 2004. Short PDF presentation.
The Cross-Polytope with Peaks (java applet).
Computation and Stability of Nash Equilibria and Applications to the Modeling of the Electrical Energy Generation Market (in Spanish).
Math. Eng. Thesis, Department of Mathematical Engineering, University of Chile, Santiago, Chile, August 2002.

Teaching

Some of my Friends / Collaborators

Joseph Anderson, Mikhail Belkin, David Cash, Bruno Codenotti, Jie Cui, Amit Deshpande, Navin Goyal, Alejandro Jofré, Ravi Kannan, Abhisek Kundu, Nelson Morales, Patricio Ramírez, Roberto Rondanelli, Marcos Sotomayor, Alejandro Toriello, Kasturi Varadarajan, Santosh Vempala, Juan Pablo Vielma, Grant Wang, Xuancheng Shao, James Voss.