most citedFrom Nesterov's Estimate Sequence to Riemannian Acceleration

15 citations · 28 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DS20201 cited

A simpler strong refutation of random -XOR

Kwangjun Ahn

Strong refutation of random CSPs is a fundamental question in theoretical computer science that has received particular attention due to the long-standing gap between the informati…

math.OC202011 cited

SGD with shuffling: optimal rates without component convexity and large epoch requirements

Kwangjun Ahn, Chulhee Yun, Suvrit Sra

We study without-replacement SGD for solving finite-sum optimization problems. Specifically, depending on how the indices of the finite-sum are shuffled, we consider the RandomShuf…

math.OC20201 cited

On Tight Convergence Rates of Without-replacement SGD

Kwangjun Ahn, Suvrit Sra

For solving finite-sum optimization problems, SGD without replacement sampling is empirically shown to outperform SGD. Denoting by the number of components in the cost and

math.OC202015 cited

From Nesterov's Estimate Sequence to Riemannian Acceleration

Kwangjun Ahn, Suvrit Sra

We propose the first global accelerated gradient method for Riemannian manifolds. Toward establishing our result we revisit Nesterov's estimate sequence technique and develop an al…

cs.DM2017

Computing the maximum matching width is NP-hard

Kwangjun Ahn, Jisu Jeong

The maximum matching width is a graph width parameter that is defined on a branch-decomposition over the vertex set of a graph. In this short paper, we prove that the problem of co…

cs.IT2017

Community Recovery in Hypergraphs

Kwangjun Ahn, Kangwook Lee, Changho Suh

Community recovery is a central problem that arises in a wide variety of applications such as network clustering, motion segmentation, face clustering and protein complex detection…