Jagdish Ramakrishnan In radiation therapy, the fractionation schedule, i.e. the total number of treatment days and the dose delivered per day, plays an important role in treatment outcome. In the first part of the talk, we analyze the effect of tumor repopulation on the optimal fractionation scheme. We find that …
Merve Bodur Stochastic programming is a way of dealing with uncertainty in the optimization problems. We consider two-stage stochastic programs with integer first stage and continuous second stage. It means that the decision maker must take some integer decisions before the uncertainty is revealed, then can observe the realizations and …
Sarah Rich Sometimes in life things are complicated, and we just wish they were simpler! (Am I right, ladies?) A standard approach of theoreticians is to just pretend that they *are* simpler and keep going! We’ll consider this approach in the context of models for large empirical networks, like social …
Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select coefficients, we propose an adaptive $\ell_1$-penalization methodology, where …
David Dynerman Cryo-electron microscopy (cryo-EM) is a technique for discovering the 3D structures of small molecules. To perform this 3D reconstruction a large number of 2D images taken from unknown microscope positions must be correctly positioned back in 3D space. Although these microscope positions are unknown, the common lines of …
Among the many popular techniques for reconstructing evolutionary trees from molecular sequences, so-called distance-matrix methods are typically the fastest. This speed stems from a straightforward, intuitive approach: repeated merging of the closest clusters of sequences. However, unlike more elaborate techniques such as maximum likelihood, distance-matrix methods only exploit empirical correlations …
Victor’s Abstract: How we used system programming techniques to tune convex optimization solvers. I demonstrate how understanding the hardware can influence the runtime of Nonnegative Matrix Factorization (NMF). ————————————- Gautam’s Abstract: Most metric learning methods are characterized by diverse loss functions and projection methods, which naturally begs the question: is …
Predictions in modern statistical inference problems can be increasingly understood in terms of discrete structures such as arrangements of objects in computer vision, phonemes in speech recognition, parses in natural language processing, or molecular structures in computational biology. For example, in image scene understanding one needs to jointly predict discrete …
Nikhil’s Abstract —————————— In applications ranging from communications and image processing to genetics, signals can be modeled as lying in a union of subspaces. Under this model, signal coefficients that lie in certain subspaces are active or inactive together. The potential subspaces are known in advance, but the particular set …
Song’s abstract —————————- We consider a probabilistic version of classical 0-1 packing problem, where we have a set of items with random weights and a random knapsack capacity. The objective is to choose a set of items that maximizes profit while ensuring the probability that the knapsack constraint is satisfi ed …