Data Science Seminars

The IMA Data Science Seminars are a forum for data scientists of IMA academic and industrial partners to discuss and learn about recent developments in the broad area of data science. Some of the talks will be by group members of the IMA Data Science Lab discussing recent developments in the area and possibly presenting their own work, while other talks will be by local and visiting data scientists with a few talks by external speakers.

The seminars are organized by Jeff Calder, Will Leeb, and Gilad Lerman of the School of Mathematics at the University of Minnesota, and will generally take place Tuesdays from 1:25-2:25 p.m. in Walter Library 402 for or by Zoom. Please check the individual seminar page for details

Can't attend? Watch the live-stream for seminars (if available).

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2021-2022
May 03, 2022	Free Boundary Problems on Lattices	Charles Smart (Yale University)
April 26, 2022	A Distributed Linear Solver via the Kaczmarz Algorithm	Eric Weber (Iowa State University)
April 19, 2022	A Characteristics-based Approach to Computing Tukey Depths	Martin Molina-Fructuoso (North Carolina State University)
April 12, 2022	How Well Can We Generalize Nonlinear Learning Models in High Dimensions??	Inbar Seroussi (Weizmann Institute of Science)
April 05, 2022	Method of Moments: From Sample Complexity to Efficient Implicit Computations	Joao Pereira (The University of Texas at Austin)
March 29, 2022	Relaxing Gaussian Assumptions in High Dimensional Statistical Procedures	Larry Goldstein (University of Southern California)
March 22, 2022	Using Artificial Intelligence to Model and Support the Management of Multimorbid Patients	Martin Michalowski (University of Minnesota, Twin Cities)
March 15, 2022	Auto-differentiable Ensemble Kalman Filters	Daniel Sanz-Alonso (University of Chicago)
March 01, 2022	On Multiclass Adversarial Training, Perimeter Minimization, and Multimarginal Optimal Transport Problems	Nicolas Garcia Trillos (University of Wisconsin, Madison)
February 22, 2022	Integrative Discriminant Analysis Methods for Multi-view Data	Sandra Safo (University of Minnesota, Twin Cities)
February 15, 2022	Graph Clustering Dynamics: From Spectral to Mean Shift	Katy Craig (University of California, Santa Barbara)
February 08, 2022	Decomposing Low-Rank Symmetric Tensors	Joe Kileel (The University of Texas at Austin)
February 01, 2022	Stability and Generalization in Graph Convolutional Neural Networks	Ron Levie (Ludwig-Maximilians-Universität München)
January 25, 2022	Intelligent Randomized Algorithms for the Low CP-Rank Tensor Approximation Problem	Alex Gittens (Rensselaer Polytechnic Institute)
December 14, 2021	New Methods for Disease Prediction using Imaging and Genomics	Eran Halperin (UnitedHealth Group)
November 23, 2021	The Scattering Transform for Texture Synthesis and Molecular Generation	Michael Perlmutter (University of California, Los Angeles)
November 09, 2021	Non-Parametric Estimation of Manifolds from Noisy Data	Yariv Aizenbud (Yale University)
October 19, 2021	Data depths meet Hamilton-Jacobi equations	Ryan Murray (North Carolina State University)
October 12, 2021	Organizational Collaboration with Assisted Learning	Jie Ding (University of Minnesota, Twin Cities)
October 05, 2021	Scalable and Sample-Efficient Active Learning for Graph-Based Classification	Kevin Miller (University of California, Los Angeles)
September 28, 2021	Standardizing the Spectra of Count Data Matrices by Diagonal Scaling	Boris Landa (Yale University)
September 21, 2021	Handling model uncertainties via informative Goodness-of-Fit	Sara Algeri (University of Minnesota, Twin Cities)
September 14, 2021	PDE-inspired Methods for Graph-based Semi-supervised Learning	Jeff Calder (University of Minnesota, Twin Cities)

2020-2021
May 18, 2021	Measuring the Happiness, Health, & Stories of Society through the Sociotechnical Dynamics of Social Media and Fiction	Chris Danforth (University of Vermont)
May 04, 2021	Order in Disorder: Modeling the Crumpling Dynamics of Thin Sheets	Jovana Andrejevic (Harvard University)
April 27, 2021	Polynomial Time Guarantees for the Burer-Monteiro Method	Diego Cifuentes (Massachusetts Institute of Technology)
April 20, 2021	Machine Learning Techniques for High-Dimensional Optimal Transport	Lars Ruthotto (Emory University)
April 13, 2021	Quantile-based Iterative Methods for Corrupted Systems of Linear Equations	Elizaveta Rebrova (University of California, Los Angeles)
April 06, 2021	The Ramanujan Machine: Using Algorithms for the Discovery of Conjectures on Mathematical Constants	Ido Kaminer (Technion-Israel Institute of Technology)
March 30, 2021	Deep Networks and the Multiple Manifold Problem	John Wright (Columbia University)
March 23, 2021	Adapting the Metropolis Algorithm	Jeffrey Rosenthal (University of Toronto)
March 16, 2021	Consistent Sparse Deep Learning: Theory and Computation	Faming Liang (Purdue University)
March 02, 2021	Coordinate Methods for Solving Eigenvalue Problems in High Dimensions	Jianfeng Lu (Duke University)
February 23, 2021	Ultrametric Gromov-Hausdorff and Gromov-Wasserstein Distances	Facundo Mémoli (The Ohio State University)
February 16, 2021	Learning the Manifold of Molecular Structures in Cryo-EM	Joakim Anden (Royal Institute of Technology (KTH))
February 09, 2021	Using Telco Data to Fight Epidemics	Kenth Monsen (Telenor Research)
February 02, 2021	Regression of Functions on Low-dimensional Manifolds by Neural Networks	Wenjing Liao (Georgia Institute of Technology)
January 26, 2021	An Optimal Transport Perspective on Uncertainty Propagation	Amir Sagiv (Columbia University)
January 19, 2021	Quantum Compiler for Classical Dynamical Systems	Dimitris Giannakis (Courant Institute of Mathematical Sciences)
December 15, 2020	Estimation of Manifolds from Point Clouds: Building Models from Data	Barak Sober (Duke University)
December 08, 2020	Understanding Convolutional Neural Networks Through Signal Processing	Matthew Hirn (Michigan State University)
December 01, 2020	Filter-decomposed Convolution in Deep Neural Networks: On Groups, Graphs, and Across Domains	Xiuyuan Cheng (Duke University)
November 24, 2020	Multiway Tensor Analysis with Neuroscience Applications	Gal Mishne (University of California, San Diego)
November 17, 2020	Fast Statistical and Geometric Distances Between Families of Distributions	Alexander Cloninger (University of California, San Diego)
November 10, 2020	Natural Graph Wavelet Packets	Naoki Saito (University of California, Davis)
November 03, 2020	Machine Learning Methods for Solving High-dimensional Mean-field Game Systems	Levon Nurbekyan (University of California, Los Angeles)
October 27, 2020	Clustering High-dimensional Data with Path Metrics: A Balance of Density and Geometry	Anna Little (The University of Utah)
October 20, 2020	How COVID-19 has Changed the World and What the Future Holds	Michael Osterholm (University of Minnesota, Twin Cities)
October 13, 2020	Geometric Methods in Statistics, Optimization, and Sampling	Tyler Maunu (Massachusetts Institute of Technology)
October 06, 2020	Large-Scale Semi-supervised Learning via Graph Structure Learning over High-dense Points	Li Wang (University of Texas at Arlington)
September 29, 2020	Multi-Perspective, Simultaneous Embedding and Theoretically Guaranteed Projected Power Method for the Multi-way Matching Problem	Vahan Huroyan (University of Arizona)
September 22, 2020	Matrix Denoising with Weighted Loss	William Leeb (University of Minnesota, Twin Cities)
September 08, 2020	Does Deep Learning Solve the Phase Retrieval Problem?	Ju Sun (University of Minnesota, Twin Cities)

2019-2020
August 18, 2020	Fairness, Accountability, and Transparency: (Counter)-Examples from Predictive Models in Criminal Justice	Kristian Lum (University of Pennsylvania)
August 04, 2020	A Network Science Approach for Controlling Epidemic Outbreaks	Anil Vullikanti (University of Virginia)
June 23, 2020	Computational Science for COVID-19 Pandemic Planning and Response	Madhav Marathe (University of Virginia)
June 09, 2020	Data and Models for COVID-19 Decision-Making	Forrest Crawford (Yale University)
May 19, 2020	Transmission Dynamics of Influenza and SARS-CoV-2: Environmental Determinants, Inference and Forecast	Jeffrey Shaman (Columbia University)
March 03, 2020	“Living” 3D World Models Leveraging Crowd Sourced Data	Jan-Michael Frahm (Facebook)
February 25, 2020	Making Small Spaces Feel Large: Practical Illusions in Virtual Reality	Evan Rosenberg (University of Minnesota, Twin Cities)
February 18, 2020	From Clustering with Graph Cuts to Isoperimetric Inequalities: Quantitative Convergence Rates of Cheeger Cuts on Data Clouds	Nicolas Garcia Trillos (University of Wisconsin, Madison)
February 11, 2020	Function Space Metropolis-Hastings Algorithms with Non-Gaussian Priors	Bamdad Hosseini (California Institute of Technology)
February 04, 2020	Different Aspects of Registration Problem	Yuehaw Khoo (University of Chicago)
January 28, 2020	SEMINAR IS CANCELED - Machine Learning Meets Societal Values	Steven Wu (University of Minnesota, Twin Cities) - SEMINAR IS CANCELED
January 21, 2020	Linear Unbalanced Optimal Transport	Matthew Thorpe (University of Cambridge)
December 06, 2019	Probabilistic Preference Learning with the Mallows Rank Model for Incomplete Data	Arnoldo Frigessi (Oslo University Hospital)
December 03, 2019	Exploiting Group and Geometric Structures for Massive Data Analysis	Zhizhen (Jane) Zhao (University of Illinois at Urbana-Champaign)
November 26, 2019	Information Flow and Security Aspects in 1-2-1 Networks	Martina Cardone (University of Minnesota, Twin Cities)
November 19, 2019	Robust Representation for Graph Data	Dongmian Zou (University of Minnesota, Twin Cities)
November 12, 2019	Latent Factor Models for Large-scale Data	Xiaoou Li (University of Minnesota, Twin Cities)
November 05, 2019	Topics in Sparse Recovery via Constrained Optimization: Least Sparsity, Solution Uniqueness, and Constrained Exact Recovery	Seyedahmad Mousavi (University of Minnesota, Twin Cities)
October 29, 2019	Highly Likely Clusterable Data With No Cluster	Mimi Boutin (Purdue University)
October 22, 2019	Convergence Rates and Semiconvexity Estimates for the Continuum Limit of Nondominated Sorting	Brendan Cook (University of Minnesota, Twin Cities)
October 15, 2019	Simple Approaches to Complicated Data Analysis	Deanna Needell (University of California, Los Angeles)
October 08, 2019	Parallel Transport Convolutional Neural Networks on Manifolds	Rongjie Lai (Rensselaer Polytechnic Institute)
October 01, 2019	Citizen Science and Machine Learning at Zooniverse	Darryl Wright (University of Minnesota, Twin Cities)
September 24, 2019	The Geometry of Ambiguity in One-dimensional Phase Retrieval	Dan Edidin (University of Missouri)
September 17, 2019	Optimal Recovery under Approximability Models, with Applications	Simon Foucart (Texas A & M University)
September 10, 2019	Taming Nonconvexity: From Smooth to Nonsmooth Problems and Beyond	Ju Sun (University of Minnesota, Twin Cities)
September 03, 2019	Where and What to Look: Learning to Understand the Visual World in Autistic Brains	Catherine Zhao (University of Minnesota, Twin Cities)

2018-2019
May 06, 2019	Robust Accelerated Gradient Methods	Mert Gurbuzbalaban (Rutgers, The State University Of New Jersey)
April 29, 2019	Solving Multiscale Problems with Subsampled Data by Integrating PDE Analysis with Data Science	Thomas Hou (California Institute of Technology)
April 22, 2019	How Hard is it to Fool a Neural Net? A Mathematical Look at Adversarial Examples	Tom Goldstein (University of Maryland)
April 15, 2019	Recent Advances in Wasserstein Distributionally Robust Optimization	Rui Gao (The University of Texas at Austin)
April 08, 2019	A Brief Overview of Quantum Computing	Vlad Pribiag (University of Minnesota, Twin Cities)
April 01, 2019	How to Deal with Big Data? Understanding Large-scale Distributed Regression	Edgar Dobriban (Wharton School of the University of Pennsylvania)
March 25, 2019	Recommendation Systems in Real Life	Mark Hsiao (Netflix, Inc)
March 11, 2019	Robust and Phaseless PCA (and Subspace Tracking)	Namrata Vaswani (Iowa State University)
March 04, 2019	Peculiar Properties of Locally Linear Embedding -- Toward Theoretical Understanding of Unsupervised Learning	Hau-tieng Wu (Duke University)
February 25, 2019	Strong Coresets for k-Median and Subspace Approximation: Goodbye Dimension	David Woodruff (Carnegie Mellon University)
February 18, 2019	Graph Convolutional Neural Network via Scattering	Dongmian Zou (University of Minnesota, Twin Cities)
February 11, 2019	Style Transfer by Relaxed Optimal Transport and Self-Similarity	Greg Shakhnarovich (Toyota Technological Institute at Chicago)
February 04, 2019	Gromov-Monge Quasi Metrics and Distance Distributions	Tom Needham (The Ohio State University)
January 28, 2019	Data-Driven Distributionally Robust Appointment Scheduling	Guanglin Xu (University of Minnesota, Twin Cities)
December 10, 2018	Stratifying High-Dimensional Data Based on Proximity to the Convex Hull Boundary	Lori Ziegelmeier (Macalester College)
November 29, 2018	Interpolative Decomposition and its Applications (Math Dept Colloquium Lecture)	Lexing Ying (Stanford University)
November 28, 2018	Convex Relaxation Approaches for Strictly Correlated Density Functional Theory	Lexing Ying (Stanford University)
November 26, 2018	Solving PDEs with Deep Learning	Lexing Ying (Stanford University)
November 19, 2018	Lipschitz Regularized Deep Neural Networks Converge and are Robust to Adversarial Perturbations	Adam Oberman (McGill University)
November 12, 2018	Learning from Highly Correlated Features using Graph Total Variation	Rebecca Willett (University of Chicago)
November 05, 2018	Solving Infinite Dimensional Optimization Problems with Convergence Guarantees	Matthew Jacobs (University of California, Los Angeles)
October 29, 2018	A Picture of the Energy Landscape of Deep Neural Networks	Pratik Chaudhari (California Institute of Technology)
October 22, 2018	Large Sample Asymptotics of Graph-based Methods in Machine Learning: Mathematical Analysis and Implications	Nicolas Garcia-Trillos (University of Wisconsin, Madison)
October 15, 2018	Free Component Analysis	Raj Nadakuditi (University of Michigan)
October 08, 2018	A PDE Approach to a Prediction Problem Involving Randomized Strategies	Nadejda Drenska (University of Minnesota, Twin Cities)
October 01, 2018	Scalable Collaboration for Data Science Done in Open Source Tools and Frameworks	Tyler Whitehouse (Gigantum)
September 24, 2018	Genetics of mRNA and Protein Expression in Large Yeast Populations	Frank Albert (University of Minnesota, Twin Cities)
September 17, 2018	The Role of the Translation Distribution in Multi-reference Alignment	William Leeb (University of Minnesota, Twin Cities)
August 10, 2018	Mathematics of Big Data & Machine Learning	Jeremy Kepner (Massachusetts Institute of Technology)

2017-2018
June 05, 2018	Mathematical Modeling of Urban Air Quality: A Case Study for Medellin, Colombia	Olga Lucia Quintero Montoya (Universidad EAFIT)
May 08, 2018	Objective Functionals of Machine Learning on Graphs and their Continuum Limits	Dejan Slepcev (Carnegie Mellon University)
May 01, 2018	Application of artificial intelligence to the standard 12 lead ECG to identify people with left ventricular dysfunction	Zachi Attia
April 26, 2018	Phase transitions and conic geometry	Joel Tropp (California Institute of Technology)
April 24, 2018	Sketchy decisions: Low-rank convex matrix optimization with optimal storage	Joel Tropp (California Institute of Technology)
April 23, 2018	Applied Random Matrix Theory	Joel Tropp (California Institute of Technology)
April 17, 2018	Population Genomics of Host-microbiome Interactions	Ran Blekhman (University of Minnesota, Twin Cities)
April 10, 2018	Human Activity Computing from Inside-out and Outside-in Visual Data	Hyun Soo Park (University of Minnesota, Twin Cities)
March 27, 2018	Primal-Dual Optimization Algorithms Over Riemannian Manifolds: An Iteration Complexity Analysise	Junyu Zhang (University of Minnesota, Twin Cities)
March 20, 2018	Accelerated Gradient PDE's: The active contour case	Anthony Yezzi (Georgia Institute of Technology)
February 20, 2018	Mixed 0-1 linear programs with uncertain objectives: A data-driven approach	Guanglin Xu (University of Minnesota, Twin Cities)
February 06, 2018	Bandwidth selection for kernel density estimators of multivariate level sets and highest density regions	Charles Doss (University of Minnesota, Twin Cities)
January 30, 2018	Implicit Regularization in Nonconvex Statistical Estimation	Yuxin Chen (Princeton University)
January 16, 2018	Distributed and Learning Based Methods for Optimizing Non-convex Problems	Mingyi Hong (University of Minnesota, Twin Cities)
December 12, 2017	New Progress on Stochastic Variance-Reduced Methods in Machine Learning: Adaptive Restart and Distributed Optimization	Qihang Lin (The University of Iowa)
December 08, 2017	Optimal Prediction in the Linearly Transformed Spiked Model	William Leeb (Princeton University)
November 28, 2017	Online Change-point Detection in High Dimensional Gaussian Graphical Models	Hossein Keshavarz (University of Minnesota, Twin Cities)
November 21, 2017	Application of Fluid Dynamics to the Cardiovascular Surgery: Mathematical Science for the Profound Insight into Cardiovascular Disease and for the Surgical Planning	Keiichi Itatani (Kyoto Prefectural University of Medicine)
October 31, 2017	Multireference Alignment without Alignment	Nicolas Boumal (Princeton University)
October 24, 2017	Optimal Control of Nonholonomic Mechanical Systems	Stuart Rogers (University of Minnesota, Twin Cities)
October 10, 2017	Community Structure in Stochastic Networks	Chao Gao (University of Chicago)
October 03, 2017	Deep Compressed Sensing	Paul Hand (Rice University)
September 26, 2017	Lipschitz bounds for general convolutional neural networks	Dongmian Zou (University of Minnesota, Twin Cities)
September 19, 2017	Quadratic Assignment on Different Data Models	Soledad Villar (New York University)

2016-2017
May 09, 2017	A Well-Tempered Landscape for Non-convex Robust Subspace Recovery	Tyler Maunu (University of Minnesota, Twin Cities)
May 02, 2017	Using Cover-Trees and Friends for Machine Learning with the CDER algorithm	Abraham Smith (University of Wisconsin-Stout)
April 18, 2017	Exploiting Data-Sparse Structures in Numerical Linear Algebra	Yuanzhe Xi (University of Minnesota, Twin Cities)
April 11, 2017	Dirichlet Graph Partitions	Braxton Osting (The University of Utah)
March 23, 2017	Algebraic and Computational Aspects of Tensors	Ke Ye (University of Chicago)
March 21, 2017	Improved Passive Microwave Retrievals of Precipitation from Space Using Sparse Approximation	Ardeshir Ebtehaj (University of Minnesota, Twin Cities)
March 10, 2017	The Generalization Performance of the Random Fourier Features Method	Anna Gilbert (University of Michigan)
March 07, 2017	PDE Scaling Limits in Semi-Supervised Learning	Jeff Calder (University of Minnesota, Twin Cities)
February 28, 2017	Methods and Applications for Precision Microbiome Quantitation	Dan Knights (University of Minnesota, Twin Cities)
February 21, 2017	“Big Data” in Image Analysis	Thomas Pengo (University of Minnesota, Twin Cities)
February 07, 2017	Dictionary Design for Graph Signal Processing	David Shuman (Macalester College)
January 24, 2017	What is special about mining spatial and spatio-temporal datasets?	Shashi Shekhar (University of Minnesota, Twin Cities)
December 05, 2016	Incorporation of Geometry into Learning Algorithms and Medicine	Alexander Cloninger (Yale University)
December 02, 2016	Elliptic PDEs and Diffusion: Short Proofs by Counting Particles and Applications	Stefan Steinerberger (Yale University)
November 29, 2016	Three-Dimensional Covariance Estimation from Noisy Tomographic Projections	Joakim Anden (Princeton University)
November 15, 2016	Orthogonal Matrix Retrieval in Cryo-electron Microscopy	Teng Zhang (University of Central Florida)
October 28, 2016	Clustering with an Oracle	Arya Mazumdar (University of Massachusetts)
October 25, 2016	Differentiated HIV Viral Load Monitoring in Resource Limited Settings: An Economic Analysis	Diana Negoescu (University of Minnesota, Twin Cities)
October 11, 2016	The Population Connectome: Information Theoretical Models for Predicting and Controlling Population Patterns	Matteo Convertino (University of Minnesota, Twin Cities)
October 07, 2016	Optimality and Sub-optimality of Principal Component Analysis for Spiked Random Matrices	Afonso Bandeira (Courant Institute of Mathematical Sciences)
September 30, 2016	Vector Diffusion Maps and the Graph Connection Laplacian	Amit Singer (Princeton University)
September 29, 2016	The Mathematics of Cryo-electron Microscopy	Amit Singer (Princeton University)
September 27, 2016	PCA from Noisy Linearly Reduced Measurements	Amit Singer (Princeton University)
September 20, 2016	Limiting Spectrum of Random Kernel Matrices	Xiuyuan Cheng (Yale University)
September 09, 2016	Unsupervised Ensemble Learning	Boaz Nadler (Weizmann Institute of Science)

2015-2016
May 03, 2016	New Variants and Convergence Properties of the Alternating Direction Method of Multipliers (ADMM)	Shuzhong Zhang (University of Minnesota, Twin Cities)
April 26, 2016	Embedding of Riemannian Manifolds and its Application to Image Denoising	Chen-Yun Lin (University of Toronto)
April 19, 2016	Structure-Based Comparisons for Sequential Data	Katherine Kinnaird (Macalester College)
April 05, 2016	Quantile Regression Analysis of Heterogeneous Data in Ultra-high Dimension	Lan Wang (University of Minnesota, Twin Cities)
March 29, 2016	Connecting SEER Data and Biological Mechanisms in Oral Cancer	Jasmine Foo (University of Minnesota, Twin Cities)
March 22, 2016	Recent Advances in Recommender Systems and Future Directions	George Karypis (University of Minnesota, Twin Cities)
March 08, 2016	Incremental Methods for Additive Convex Cost Optimization	Asuman Ozdaglar (Massachusetts Institute of Technology)
March 01, 2016	Adaptive Sketching and Validation to Learn from Large-Scale Data	Georgios Giannakis (University of Minnesota, Twin Cities)
February 23, 2016	Stochastic Geometry and Wireless Networks	Francois Baccelli (The University of Texas at Austin)
February 16, 2016	Envelopes: Methods for Improving Efficiency in Multivariate Statistics	Dennis Cook (University of Minnesota, Twin Cities)
February 09, 2016	Indirect Multivariate Response Linear Regression	Adam Rothman (University of Minnesota, Twin Cities)
February 02, 2016	Methodological Aspects of Predictive Data Analytics and VC-theory	Vladimir Cherkassky (University of Minnesota, Twin Cities)
January 19, 2016	Fast Algorithm for Robust Subspace Recovery	Tyler Maunu (University of Minnesota, Twin Cities)
December 15, 2015	Computational Analysis and Applications of Diffusion MRI	Christophe Lenglet (University of Minnesota, Twin Cities)
December 08, 2015	Locating Outliers in Large Matrices with Adaptive Compressive Sampling	Jarvis Haupt (University of Minnesota, Twin Cities)
December 01, 2015	Understanding Global Change: Opportunities and Challenges for Data Driven Research	Vipin Kumar (University of Minnesota, Twin Cities)
November 24, 2015	Reconstructing the Farm, Keeping an Eye on the Environment (with Robots)	Volkan Isler (University of Minnesota, Twin Cities)
November 10, 2015	Sampling Algorithms in Numerical Linear Algebra and their Applications	Yousef Saad (University of Minnesota, Twin Cities)
October 27, 2015	Gauges, Sparsity, and Spectral Optimization	Michael Friedlander (University of California)
October 22, 2015	Special Seminar: Some Statistical Problems Related to Big Data	Boaz Nadler (Weizmann Institute of Science)
October 13, 2015	Estimation with Norm Regularization: A Geometric Perspective	Arindam Banerjee (University of Minnesota, Twin Cities)
October 06, 2015	Low-complexity Modeling of Partially Available Second-order Statistics via Matrix Completion	Mihailo Jovanovic (University of Minnesota, Twin Cities)
September 22, 2015	Another Look at DWD: Thrifty Algorithm and Bayes Risk Consistency in RHS	Hui Zou (University of Minnesota, Twin Cities)
September 08, 2015	Seminar Planning and Decision Making	Gilad Lerman (University of Minnesota, Twin Cities), Jeffrey Moulton (University of Minnesota, Twin Cities)
December 31, 1969