16 citations · 78 across the 43 of their papers we have counts for
4 papers · 2 filters
Provable learning of Noisy-or Networks
Sanjeev Arora, Rong Ge, Tengyu Ma +1
Many machine learning applications use latent variable models to explain structure in data, whereby visible variables (= coordinates of the given datapoint) are explained as a prob…
Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates
Yuanzhi Li, Yingyu Liang, Andrej Risteski
Non-negative matrix factorization is a popular tool for decomposing data into feature and weight matrices under non-negativity constraints. It enjoys practical success but is poorl…
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods
Yuanzhi Li, Andrej Risteski
The well known maximum-entropy principle due to Jaynes, which states that given mean parameters, the maximum entropy distribution matching them is in an exponential family, has bee…
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods
Andrej Risteski
We consider the problem of approximating partition functions for Ising models. We make use of recent tools in combinatorial optimization: the Sherali-Adams and Lasserre convex prog…