Matteo Bergamaschi

Beyond Local Influence: Improved Bounds, Exact Models and Efficient Algorithms for Component-Based Diffusion in Networks

Categories Combinatorial Optimization, Network Optimization Tags , ,

Diffusion in networks is often modeled as a local neighbor-based process: a node becomes active as a result of influence exerted by its active neighbors. However, in many technological and communication settings, adoption is driven not only by local influence, but by access to sufficiently large active connected regions. This paper studies such component-based diffusion … Read more

Probabilistic Iterative Hard Thresholding for Sparse Learning

Categories Nonlinear Optimization, Stochastic Programming Tags , ,

For statistical modeling wherein the data regime is unfavorable in terms of dimensionality relative to the sample size, finding hidden sparsity in the ground truth can be critical in formulating an accurate statistical model. The so-called “l0 norm”, which counts the number of non-zero components in a vector, is a strong reliable mechanism of enforcing … Read more