Systems | Information | Learning | Optimization
 

One Relaxation to Rule Them All: Strong Convex Nonlinear Relaxations of the Pooling Problem

Video Recording: https://vimeo.com/153826086 Our quest is to derive convex relaxations for the pooling problem, a nonconvex production planning problem in which products are mixed in intermediate pools in order to meet quality targets at their destinations. The story begins with a description of the problem and discussion of state-of-the-art solution …

Towards Next Generation 3D Cameras

Video Recording: https://vimeo.com/154227289 We are in the midst of a 3D revolution. Robots enabled by 3D cameras are beginning to autonomously drive cars, perform surgeries, and manage factories. However, when deployed in the real-world, these cameras face several challenges that prevent them from measuring 3D shape reliably. These challenges include …

A Matrix Factorization Approach to Multiple Imputation and DCM Bandits: Learning to Rank with Multiple Clicks

A Matrix Factorization Approach to Multiple Imputation: https://vimeo.com/155397341 Almost all empirical analysis in the social sciences is plagued with the problem of missing data, for instance in opinion surveys, some respondents choose not to answer certain questions, or in longitudnal surveys respondents in the pilot round may drop out in …

SMART: The Stochastic Monotone Aggregated Root-Finding Algorithm

Video: https://vimeo.com/156600995 We introduce the Stochastic Monotone Aggregated Root-Finding (SMART) algorithm, a new randomized operator-splitting scheme for finding roots of finite sums of operators. These algorithms are similar to the growing class of incremental aggregated gradient algorithms, which minimize finite sums of functions; the difference is that we replace gradients …

Geometry and Topology in Inference

video: https://vimeo.com/156713270 In the first part of the talk we state how geometry can be used for modeling mixtures of subspaces as well as analyzing online (stochastic) optimization algorithms.  We introduce a Bayesian model for inferring mixtures of subspaces of different dimensions. The key challenge in such a model is …

A Control Perspective on Optimization of Strongly Convex Functions

Video: https://vimeo.com/158060000 We present our recent progress on adopting control tools for optimization of strongly convex functions. First, built upon the existing integral quadratic constraint (IQC) analysis framework of first-order optimization methods, we further develop an IQC approach to analyze the stochastic average gradient (SAG) method. The SAG method is …

Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls and Efficient Bregman Projections onto the Permutahedron and Related Polytopes

Video: https://vimeo.com/158493334 Talk 1 – Kwang-Sung Jun: Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls We introduce a new multi-armed bandit (MAB) problem in which arms must be sampled in batches, rather than one at a time. This is motivated by applications in social media monitoring and biological …

New Perspectives in Robust, High-dimensional Statistics

Video: https://vimeo.com/159423831 Robust statistics provides a powerful framework for quantifying the behavior of estimators when data are observed subject to imperfections that deviate from standard modeling assumptions. In this talk, we highlight recent work involving statistical theory for robust estimators in high dimensions, with applications to compressed sensing and graphical …

Following Natural Language Instructions in Unknown Environments

Video: https://vimeo.com/161102509 Natural language promises an efficient and flexible means for humans to communicate with robots, whether they are assisting the physically or cognitively impaired, or performing disaster mitigation tasks as our surrogates. Recent advancements have given rise to robots that are able to interpret natural language commands that direct …

Block CUR Decompostion: Matrix Approximation Using Groups of Columns and Inferring Relationships in High-dimensional Generalized Linear Autoregressive Processes

Video: https://vimeo.com/163595515 Urvashi Oswal – Block CUR Decomposition: Matrix Approximation using Groups of Columns A common problem in large-scale data analysis is approximating a matrix using a combination of specifically sampled rows and columns. Unfortunately, in many real-world environments, the ability to sample specific individual rows or columns of the …