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Found 7 papers, 1 papers with code
Bandits for Online Calibration: An Application to Content Moderation on Social Media Platforms
We describe the current content moderation strategy employed by Meta to remove policy-violating content from its platforms.
QUEST: Queue Simulation for Content Moderation at Scale
Moderating content in social media platforms is a formidable challenge due to the unprecedented scale of such systems, which typically handle billions of posts per day.
Learning Exponential Family Graphical Models with Latent Variables using Regularized Conditional Likelihood
Fitting a graphical model to a collection of random variables given sample observations is a challenging task if the observed variables are influenced by latent variables, which can induce significant confounding statistical dependencies among the observed variables.
Sparse and Low-Rank Tensor Decomposition
Our method relies on a reduction of the problem to sparse and low-rank matrix decomposition via the notion of tensor contraction.
Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice
This motivates us to consider the problem of low rank tensor recovery from a class of linear measurements called separable measurements.
Relative Entropy Relaxations for Signomial Optimization
This sequence of lower bounds is computed by solving increasingly larger-sized relative entropy optimization problems, which are convex programs specified in terms of linear and relative entropy functions.
Optimization and Control
Forward - Backward Greedy Algorithms for Atomic Norm Regularization
CoGEnT combines a greedy selection scheme based on the conditional gradient approach with a backward (or "truncation") step that exploits the quadratic nature of the objective to reduce the basis size.
