tschramm AT cs DOT berk
I am a Research Fellow at the Simons Institute this Fall, en route to a postdoc at Harvard and MIT.
I am freshly graduated from a PhD in the U.C. Berkeley
Theory Group, where I was advised by
Prasad Raghavendra and
I got my B.S. in CS/Math from
Harvey Mudd College,
where Ran Libeskind-Hadas kept me out of trouble.
My research interests include Spectral Algorithms, Spectral Graph Theory, Approximation Algorithms, Semidefinite Programming (especially the Sum-of-Squares Hierarchy), Random Matrices, and more.
Here is a tutorial for pronouncing my name.
Check out the "Intro to sum-of-squares" blog post I wrote for Learning With Errors, Preetum Nakkiran's new student blog.
On the power of sum-of-squares for detecting hidden structures
Prasad Raghavendra, and
in FOCS 2017.
Fast and robust tensor decomposition with applications to dictionary learning
in COLT 2017.
Strongly refuting random cSPs below the spectral threshold
in STOC 2017.
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors
with Sam Hopkins, Jonathan Shi, and David Steurer,
in STOC 2016.
On the integrality gap of degree-4 sum-of-squares for planted clique
in SODA 2016
(merge of [this] paper and [this] paper)
Invited to the SODA 2016 special issue of ACM Transactions on Algorithms.
Braess's paradox for the spectral gap in random graphs and delocalization of eigenvectors
with Ronen Eldan and
in Random Structures & Algorithms (2016).
Near optimal LP rounding algorithms for correlation clustering in complete and complete k-partite graphs
with Shuchi Chawla,
and Grigory Yaroslavtsev,
in STOC 2015.
Symmetric tensor completion from multilinear entries and learning product mixtures over the hypercube
with Benjamin Weitz.
Gap amplification for small-set expansion via random walks
with Prasad Raghavendra,
in APPROX 2014.
Global and local information in clustering labeled block models
in RANDOM 2014, and in IEEE Transactions on Information Theory (2016).