6 papers
Voting models and semilinear parabolic equations
Jing An, Christopher Henderson, Lenya Ryzhik
We present probabilistic interpretations of solutions to semi-linear parabolic equations with polynomial nonlinearities in terms of the voting models on the genealogical trees of b…
Combining resampling and reweighting for faithful stochastic optimization
Jing An, Lexing Ying
Many machine learning and data science tasks require solving non-convex optimization problems. When the loss function is a sum of multiple terms, a popular method is the stochastic…
On the gradient flow structure of the isotropic Landau equation
Jing An, Lexing Ying
We prove that the isotropic Landau equation equipped with the Coulomb potential introduced by Krieger-Strain and Gualdani-Guillen can be identified with the gradient flow of the en…
Searching for correlations in GAIA DR2 unbound star trajectories
Francesco Montanari, David Barrado, Juan García-Bellido
Scattering events with compact objects are expected in the primordial black hole (PBH) cold dark matter (CDM) scenario due to close encounters between stars and PBH in the dense en…
Global well-posedness for the Euler alignment system with mildly singular interactions
Jing An, Lenya Ryzhik
We consider the Euler alignment system with mildly singular interaction kernels. When the local repulsion term is of the fractional type, global in time existence of smooth solutio…
Stochastic modified equations for the asynchronous stochastic gradient descent
Jing An, Jianfeng Lu, Lexing Ying
We propose a stochastic modified equations (SME) for modeling the asynchronous stochastic gradient descent (ASGD) algorithms. The resulting SME of Langevin type extracts more infor…