90 citations · 332 across the 63 of their papers we have counts for
4 papers · 1 filter
Simulated Tempering Langevin Monte Carlo II: An Improved Proof using Soft Markov Chain Decomposition
Rong Ge, Holden Lee, Andrej Risteski
A key task in Bayesian machine learning is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). One prevalent example…
Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective
Vishesh Jain, Frederic Koehler, Andrej Risteski
The free energy is a key quantity of interest in Ising models, but unfortunately, computing it in general is computationally intractable. Two popular (variational) approximation sc…
Approximability of Discriminators Implies Diversity in GANs
Yu Bai, Tengyu Ma, Andrej Risteski
While Generative Adversarial Networks (GANs) have empirically produced impressive results on learning complex real-world distributions, recent works have shown that they suffer fro…
Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis
Frederic Koehler, Andrej Risteski
There has been a large amount of interest, both in the past and particularly recently, into the power of different families of universal approximators, e.g. ReLU networks, polynomi…