Campuses:

Talks

Date Title / Speaker Eventsort ascending
October 03, 2018 Spotting Influential Customers for Targeted Offers: From Social to Nonsocial
Georgia Perakis (Massachusetts Institute of Technology)
Forging a New Discipline: Data-driven Supply Chain Management
October 05, 2018 Sample-Based Optimal Pricing
Omar Besbes (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Procurement in the twenty first century: New approaches to old problems
Awi Federgruen (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 05, 2018 Omni-Channel Order Fulfillment: From Concept to Practice
Vivek Farias (Massachusetts Institute of Technology)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Behavioral Analytics for Myopic Agents
Philip Kaminsky (University of California, Berkeley)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Auction Design for ROI-Constrained Buyers
Ilan Lobel (New York University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Predicting with Proxies
Hamsa Bastani (Wharton School of the University of Pennsylvania)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Interpretable Optimal Stopping
Velibor Misic (University of California, Los Angeles)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Online Assortment Optimization with Reusable Resources
Vineet Goyal (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 A Conditional Gradient Approach for Nonparametric Estimation of Mixing Distributions
Srikanth Jagabathula (New York University)
Forging a New Discipline: Data-driven Supply Chain Management
October 03, 2018 Crowdsourcing Operations: Incentivizing Bike Angels in America
David Shmoys (Cornell University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Approximation Algorithms for Network Revenue Management
Huseyin Topaloglu (Cornell University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Smart Predict, then Optimize
Adam Elmachtoub (Columbia University)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Joint pricing and inventory control models with long lead times
Xin Chen (University of Illinois at Urbana-Champaign)
Forging a New Discipline: Data-driven Supply Chain Management
October 04, 2018 Distributionally Robust Linear and Discrete Optimization with Marginals
Karthik Natarajan (Singapore University of Technology and Design)
Forging a New Discipline: Data-driven Supply Chain Management
November 19, 2018 Lipschitz Regularized Deep Neural Networks Converge and are Robust to Adversarial Perturbations
Adam Oberman (McGill University)
Data Science Seminar
February 11, 2019 Style Transfer by Relaxed Optimal Transport and Self-Similarity
Greg Shakhnarovich (Toyota Technological Institute at Chicago)
Data Science Seminar
November 26, 2018 Solving PDEs with Deep Learning
Lexing Ying (Stanford University)
Data Science Seminar
November 28, 2018 Convex Relaxation Approaches for Strictly Correlated Density Functional Theory
Lexing Ying (Stanford University)
Data Science Seminar
November 29, 2018 Interpolative Decomposition and its Applications (Math Dept Colloquium Lecture)
Lexing Ying (Stanford University)
Data Science Seminar
March 11, 2019 Robust and Phaseless PCA (and Subspace Tracking)
Namrata Vaswani (Iowa State University)
Data Science Seminar
March 04, 2019 Peculiar Properties of Locally Linear Embedding -- Toward Theoretical Understanding of Unsupervised Learning
Hau-tieng Wu (Duke University)
Data Science Seminar
May 06, 2019 Robust Accelerated Gradient Methods
Mert Gurbuzbalaban (Rutgers, The State University Of New Jersey)
Data Science Seminar
October 15, 2018 Free Component Analysis
Raj Nadakuditi (University of Michigan)
Data Science Seminar
February 04, 2019 Gromov-Monge Quasi Metrics and Distance Distributions
Tom Needham (The Ohio State University)
Data Science Seminar
April 08, 2019 A Brief Overview of Quantum Computing
Vlad Pribiag (University of Minnesota, Twin Cities)
Data Science Seminar
October 01, 2018 Scalable Collaboration for Data Science Done in Open Source Tools and Frameworks
Tyler Whitehouse (Gigantum)
Data Science Seminar
September 24, 2018 Genetics of mRNA and Protein Expression in Large Yeast Populations
Frank Albert (University of Minnesota, Twin Cities)
Data Science Seminar
February 25, 2019 Strong Coresets for k-Median and Subspace Approximation: Goodbye Dimension
David Woodruff (Carnegie Mellon University)
Data Science Seminar
November 12, 2018 Learning from Highly Correlated Features using Graph Total Variation
Rebecca Willett (University of Chicago)
Data Science Seminar
February 18, 2019 Graph Convolutional Neural Network via Scattering
Dongmian Zou (University of Minnesota, Twin Cities)
Data Science Seminar
October 22, 2018 Large Sample Asymptotics of Graph-based Methods in Machine Learning: Mathematical Analysis and Implications
Nicolas Garcia-Trillos (University of Wisconsin, Madison)
Data Science Seminar
April 01, 2019 How to Deal with Big Data? Understanding Large-scale Distributed Regression
Edgar Dobriban (Wharton School of the University of Pennsylvania)
Data Science Seminar
March 25, 2019 Recommendation Systems in Real Life
Mark Hsiao (Netflix, Inc)
Data Science Seminar
October 29, 2018 A Picture of the Energy Landscape of Deep Neural Networks
Pratik Chaudhari (California Institute of Technology)
Data Science Seminar
August 10, 2018 Mathematics of Big Data & Machine Learning
Jeremy Kepner (Massachusetts Institute of Technology)
Data Science Seminar
April 15, 2019 Recent Advances in Wasserstein Distributionally Robust Optimization
Rui Gao (The University of Texas at Austin)
Data Science Seminar
November 05, 2018 Solving Infinite Dimensional Optimization Problems with Convergence Guarantees
Matthew Jacobs (University of California, Los Angeles)
Data Science Seminar
December 10, 2018 Stratifying High-Dimensional Data Based on Proximity to the Convex Hull Boundary
Lori Ziegelmeier (Macalester College)
Data Science Seminar
October 08, 2018 A PDE Approach to a Prediction Problem Involving Randomized Strategies
Nadejda Drenska (University of Minnesota, Twin Cities)
Data Science Seminar
April 22, 2019 How Hard is it to Fool a Neural Net? A Mathematical Look at Adversarial Examples
Tom Goldstein (University of Maryland)
Data Science Seminar
January 28, 2019 Data-Driven Distributionally Robust Appointment Scheduling
Guanglin Xu (University of Minnesota, Twin Cities)
Data Science Seminar
April 29, 2019 Solving Multiscale Problems with Subsampled Data by Integrating PDE Analysis with Data Science
Thomas Hou (California Institute of Technology)
Data Science Seminar
September 17, 2018 The Role of the Translation Distribution in Multi-reference Alignment
William Leeb (University of Minnesota, Twin Cities)
Data Science Seminar
October 17, 2018 Hands-on tutorial - Developing Python bindings
William Hart (Sandia National Laboratories), Carl Laird (Sandia National Laboratories), Jean-Paul Watson (Sandia National Laboratories)
COIN fORgery: Developing Open Source Tools for Operations Research
October 15, 2018 COIN-OR and the Optimization Suite
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 17, 2018 Reports from breakout groups
Matthias Koeppe (University of California, Davis)
COIN fORgery: Developing Open Source Tools for Operations Research
October 15, 2018 Track 1: hands-on tutorial - Version Control
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 COIN-OR interfaces: OSI, CGL
Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 15, 2018 Track 2: hands-on tutorial - Build System
Stefan Vigerske (GAMS Development Corporation)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 Panel: Developing generic interfaces
Oscar Dowson (Northwestern University), Horand Gassmann (Dalhousie University), Bjarni Kristjansson (Maximal Software, Ltd), Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 15, 2018 Project Management
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 Lunch - on your own or with breakout group on the future of the COIN-OR Foundation
Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 15, 2018 Build Tools
Stefan Vigerske (GAMS Development Corporation)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 Track 2: Special interest group on interfaces
Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 17, 2018 Python bindings for Ipopt
Carl Laird (Sandia National Laboratories)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Continuous integration and testing in COIN-OR
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 Track 1: hands-on tutorial - Bug squashing: from TRAC to Github
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Some Perspectives on Testing and Continuous Integration for Open Source Software
William Hart (Sandia National Laboratories), John Siirola (Sandia National Laboratories)
COIN fORgery: Developing Open Source Tools for Operations Research
October 18, 2018 Reports from breakout groups
Matthias Koeppe (University of California, Davis)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Documentation in the modern age
Giacomo Nannicini (IBM)
COIN fORgery: Developing Open Source Tools for Operations Research
October 19, 2018 Panel: Research software challenges
Matthias Koeppe (University of California, Davis), Ted Ralphs (Lehigh University), Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Lunch - on your own or with breakout group on website management
Andrew Mason (University of Auckland)
COIN fORgery: Developing Open Source Tools for Operations Research
October 19, 2018 Reports from breakout groups
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Track 1: hands-on tutorial - Unit testing and CI in C++/Python
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 19, 2018 Lunch breakout group on the future of Clp/Cbc
Ted Ralphs (Lehigh University)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Track 2: Special interest group on big-picture documentation issues
Giacomo Nannicini (IBM)
COIN fORgery: Developing Open Source Tools for Operations Research
October 16, 2018 Reports from breakout groups
Matthias Koeppe (University of California, Davis)
COIN fORgery: Developing Open Source Tools for Operations Research
October 17, 2018 Python bindings: Overview and challenges
Jean-Paul Watson (Sandia National Laboratories)
COIN fORgery: Developing Open Source Tools for Operations Research
October 17, 2018 Alternative packages for Python bindings
William Hart (Sandia National Laboratories)
COIN fORgery: Developing Open Source Tools for Operations Research
October 17, 2018 Lunch - on your own or with breakout group on licensing issues
Matthew Saltzman (Clemson University)
COIN fORgery: Developing Open Source Tools for Operations Research
April 09, 2018 Deriving stochastic heat conduction model from molecular dynamics
Xiantao Li (The Pennsylvania State University)
Working Group on Mathematical Modeling of Finite-temperature Coarse-graining
April 09, 2018 Entropic barriers and dynamical coarse-graining
Thomas Hudson (University of Warwick)
Working Group on Mathematical Modeling of Finite-temperature Coarse-graining
April 10, 2018 Path-space information metrics and variational inference for coarse-grained non-equilibrium steady states
Petr Plechac (University of Delaware)
Working Group on Mathematical Modeling of Finite-temperature Coarse-graining
April 10, 2018 Spatial Decomposition of Entropy in the Harmonic Approximation. Applications??
Christoph Ortner (University of Warwick)
Working Group on Mathematical Modeling of Finite-temperature Coarse-graining
April 09, 2018 Coarse grained models for variance reduction in particle methods
David Aristoff (Colorado State University)
Working Group on Mathematical Modeling of Finite-temperature Coarse-graining
June 27, 2018 Anomalous diffusion in two homogenization problems
Gautam Iyer (Carnegie Mellon University)
Working Group on Multiscale Strategies
June 20, 2018 A Hamilton-Jacobi theory for the hydrodynamic limit large deviation of nonlinear heat equation from stochastic Carleman particles
Jin Feng (University of Kansas)
Working Group on Multiscale Strategies
June 20, 2018 On fluctuations in particle systems and their scaling limits
Johannes Zimmer (University of Bath)
Working Group on Multiscale Strategies
June 27, 2018 Stability and Convergence of the String Method
Brian Van Koten (University of Chicago)
Working Group on Multiscale Strategies
June 26, 2018 Model-Form Uncertainty Quantification for Probabilistic Graphical Models and Applications to Electronic-Structure-based Chemical Kinetics
Markos Katsoulakis (University of Massachusetts)
Working Group on Multiscale Strategies
June 18, 2018 Lecture
Richard James (University of Minnesota, Twin Cities)
Working Group on Multiscale Strategies
June 26, 2018 A Survey of Recent Results on Mass Transport
Gideon Simpson (Drexel University)
Working Group on Multiscale Strategies
June 19, 2018 Mechanics using quantum mechanics
Phanish Suryanarayana (Georgia Institute of Technology)
Working Group on Multiscale Strategies
June 21, 2018 Symmetry, deformations and the search for unprecedented materials from first principles
Amartya Banerjee (Lawrence Berkeley National Laboratory)
Working Group on Multiscale Strategies
June 22, 2018 Microstructure, wrinkling and origami in nematic elastomer sheets
Paul Plucinsky (University of Minnesota, Twin Cities)
Working Group on Multiscale Strategies
June 28, 2018 Mechanical Relaxation of Incommensurate 2D Heterostructures in Configuration Space
Mitchell Luskin (University of Minnesota, Twin Cities)
Working Group on Multiscale Strategies
June 25, 2018 Long time behaviour and phase transitions for the McKean-Vlasov equation
Grigorios Pavliotis (Imperial College London)
Working Group on Multiscale Strategies
June 25, 2018 Coarse-graining out of equilibrium: from particles to dissipative PDEs
Celia Reina (University of Pennsylvania)
Working Group on Multiscale Strategies
June 18, 2018 Challenges and recent progress in large-scale electronic structure calculations
Vikram Gavini (University of Michigan)
Working Group on Multiscale Strategies
October 24, 2018 GEO-AI - the birth of a new discipline
Eldad Haber (University of British Columbia)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Impact of geological stress on flow and transport in fractured media
Peter Kang (University of Minnesota, Twin Cities)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Advances in Supervised and Semi-Supervised Machine Learning for Image Analysis of Multi-Modal Geospatial Imagery Data
Saurabh Prasad (University of Houston)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Overview of today’s joint inversion methodology and its future into the machine-learning era for geophysical imaging
Monica Maceira (Oak Ridge National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 24, 2018 Machine Learning for Background Estimation in Multispectral Imagery
James Theiler (Los Alamos National Laboratory)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Fast and Accurate Maximum-Likelihood Estimation of Parameterized Spectral Densities that Jointly Characterize Bivariate Two-Dimensional Random Fields
Frederik Simons (Princeton University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 25, 2018 Regularization and Compression via Tensor Dictionaries
Misha Kilmer (Tufts University)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Hierarchical deep generative networks for Bayesian inverse problems
Pengchuan Zhang (Microsoft Research)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 23, 2018 Dictionary learning and graph signal processing on a 5200 element seismic array
Peter Gerstoft (University of California, San Diego)
Recent Advances in Machine Learning and Computational Methods for Geoscience
October 22, 2018 Geometric separation and applications to hyperspectral image analysis
Demetrio Labate (University of Houston)
Recent Advances in Machine Learning and Computational Methods for Geoscience

Pages