TA4b.2

Almost multisecant BFGS quasi-Newton method

Mokhwa Lee, Yifan Sun, Stony Brook University, United States
Session:
TA4b: Optimization Lecture
Track:
Adaptive Systems, Machine Learning, and Data Analytics
Location:
Nautilus
Presentation Time:
Tue, 29 Oct, 10:40 - 11:05 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session TA4b
TA4b.1: Difference-of-Convex Approximation Methods for the Affine Sparsity Constraints for Hierarchical Variable Selection
Chengyu Ke, American Airlines Inc., United States; Miju Ahn, Southern Methodist University, United States
TA4b.2: Almost multisecant BFGS quasi-Newton method
Mokhwa Lee, Yifan Sun, Stony Brook University, United States
TA4b.3: Discrete Aware Matrix Completion via Convexized ℓ0-Norm Approximation
Niclas Führling, Kengo Ando, Giuseppe Thadeu Freitas de Abreu, Constructor University, Germany; David Gonzalez G., Osvaldo Gonsa, Continental AG, Germany
TA4b.4: Generalized model recovery from real world data
Ayan Banerjee, Sandeep Gupta, Arizona State University, United States
Contacts