Estimation of a Low-rank Topic-Based Model for Information Cascades
We consider the problem of estimating the latent structure of a social network based on the observed information diffusion events, or _cascades_. Here for a given cascade, we only …
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Graph representation learning is a ubiquitous task in machine learning where the goal is to embed each vertex into a low-dimensional vector space. We consider the bipartite graph …
Posterior Ratio Estimation for Latent Variables
Density Ratio Estimation has attracted attention from machine learning community due to its ability of comparing the underlying distributions of two datasets. However, in some …
yulong-zhang
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator
Multi-agent reinforcement learning has been successfully applied to a number of challenging problems. Despite these empirical successes, theoretical understanding of different …
Distributed Stochastic Multi-Task Learning with Graph Regularization
We propose methods for distributed graph-based multi-task learning that are based on weighted averaging of messages from other machines. Uniform averaging or diminishing stepsize …
weiran-wang
Scalable Peaceman-Rachford Splitting Method with Proximal Terms
Along with developing of Peaceman-Rachford Splittling Method (PRSM), many batch algorithms based on it have been studied very deeply. But almost no algorithm focused on the …