NewsMachine Learning Research at IEMS
News
The IEMS department hosts a recurring meeting in which faculty present their work related to machine learning.
AUGUST 21, 2020: David Morton
Distributionally Robust Two-Stage Stochastic Programming
Distributionally Robust Stochastic Dual Dynamic Programming
JULY 24, 2020: Simge Kucukyavuz
Integer Programming for Learning Directed Acyclic Graphs from Continuous Data
Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks
On the Convexification of Constrained Quadratic Optimization Problems with Indicator Variables
Ideal Formulations for Constrained Convex Optimization Problems with Indicator Variables
A polyhedral approach to bisubmodular function minimization
JUNE 12, 2020: Noshir Contractor
Moon 2024: Translating Research to Practice
A Successful Crew Composition Countermeasure Validated in HERA
May 22, 2020: Barry Nelson
April 17, 2020: Ed Malthouse and Diego Klabjan
An Algorithm for Allocating Sponsored Recommendations and
Content: Unifying Programmatic Advertising and Recommender
Systems
Multistakeholder Recommendation with Provider Constraints
A Multistakeholder Recommender Systems Algorithm for
Allocating Sponsored Recommendations
LUCK, MACHINE LEARNING AND IEMS: You do need all three of them
FebRUARY 19, 2020: Zhaoran Wang and Jorge Nocedal
