22 citations · 57 across the 14 of their papers we have counts for
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cs.LG2022★ 2 cited
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation
Jun-Kun Wang, Andre Wibisono
We consider a setting that a model needs to adapt to a new domain under distribution shifts, given that only unlabeled test samples from the new domain are accessible at test time.…
cs.LG2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
Jun-Kun Wang, Andre Wibisono
Hamiltonian Monte Carlo (HMC) is a popular method in sampling. While there are quite a few works of studying this method on various aspects, an interesting question is how to choos…
math.OC2022★ 2 cited
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out
Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono +1
Heavy Ball (HB) nowadays is one of the most popular momentum methods in non-convex optimization. It has been widely observed that incorporating the Heavy Ball dynamic in gradient-b…