Privacy is the problem of ensuring limited leakage of information about sensitive features while sharing information (utility) about non-private features to legitimate data users. Even as differential privacy has emerged as a strong desideratum for privacy, there is also an equally strong need for context-aware utility-guaranteeing approaches in many data …
Recently, the surge of interest in deep neural learning has dramatically improved image and signal processing, which has fueled breakthroughs in many domains such as drug discovery, genomics, and automatic translation. These advances have been further applied to scientific computing and, in particular, to electronic structure computations. In this case, …
Several important families of computational and statistical results in machine learning and randomized algorithms rely on statistical independence of data. The scope of such results include the Johnson-Lindenstrauss Lemma (JLL), the Restricted Isometry Property (RIP), regression models, and stochastic optimization. In this talk, we will discuss a new result on …
Fitting a model to a collection of observations is one of the quintessential questions in statistics. The standard assumption is that the data was generated by a model of a given type (e.g., a mixture model). This simplifying assumption is at best only approximately valid, as real datasets are typically …
A restricted Boltzmann machine (RBM) is a type of undirected graphical model with one hidden and one visible layer of variables, where all variables in one layer are conditionally independent given variables in the other layer. In recent years, RBMs have risen to prominence due to their connection to deep …
We consider the global optimization of nonconvex quadratic programs and mixed-integer quadratic programs. We present a family of convex quadratic relaxations which are derived by convexifying nonconvex quadratic functions through perturbations of the quadratic matrix. We investigate the theoretical properties of these quadratic relaxations and show that they are equivalent …
In this talk, the change points of the time series of PM10 of the city of Bogotá are considered. The number of change points and their respective locations are determined using the genetic algorithm. This algorithm considers the interaction of two chromosomes (mother and father) and their mutations, to conceive new generations of descendants …
This talk will focus on how a Lagrangian perspective on dynamics is used to capture the time evolution of complex systems, e.g., granular flows, fluid-solid interaction problems, etc. In this context, the aspects that turn out to be more challenging are tied to the handling of friction, contact, geometry, large …
Evolutionary relationships between species are often depicted using a phylogenetic tree. The structure of the tree depends on the species’ genomes. A common method for deducing the tree is to analyze the genomic evolution of particular loci, but under a basic assumption of gene duplication and loss, the tree implied …
Many engineering applications such as infrastructure operation and model predictive control (MPC) involve solving similar optimization problems over and over and over and over again, with slightly varying input parameters. Electric grid optimization, which is influenced by variable renewable energy generation, is a prominent example. In this talk, we consider …