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Program for stream Advances in mathematical optimization for machine learning
Wednesday
Wednesday, 10:15  11:30
WC02: Advances in mathematical optimization for machine learning and data analysis  Part I
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):
Le Thi Khanh Hien

An adaptive subsampled Hessianfree optimization method for statistical learning.
Jeremy RIEUSSEC, Fabian Bastin, Jean LaprésChartrand, Loïc ShiGarrier 
An Inertial Newton Algorithm for Deep Learning
Camille Castera, Jerome Bolte, Cédric Févotte, Edouard Pauwels 
An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization
Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis
Wednesday, 11:45  13:00
WD02: Advances in mathematical optimization for machine learning and data analysis  Part II
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs
Manon Romain 
An adaptive, accelerated algorithm for stochastic constrained convex optimization
Ali Kavis, Kfir Levy, Francis Bach, Volkan Cevher 
Recent Advanced in the Theory of (Adaptive) Stochastic Gradient Methods
Vivak Patel
Wednesday, 15:45  17:30
WF02: Beyond Firstorder Optimization Methods for Machine Learning  Part I
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):
Fred Roosta, Albert Berahas

Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization
Albert Berahas, Frank E. Curtis 
Stochastic Polyak Stepsize for SGD: An Adaptive Learning Rate for Fast Convergence
Nicolas Loizou 
Systematic Secondorder Methods for Training, Designing, and Deploying Neural Networks
Amir Gholami 
Distributed Learning of Deep Neural Networks using Independent Subnet Training
Anastasios Kyrillidis
Thursday
Thursday, 9:00  10:40
TA02: Nonlinear Composite and Constrained Optimization  Part I
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

Proximal alternating minimization for solving discrete MumfordShah and AmborsioTortorelli models
Hoang Trieu Vy LE, Marion Foare, Nelly Pustelnik 
Random extrapolation for primaldual coordinate descent
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher 
PrimalDual Proximal Splitting Algorithms for LargeScale Convex Optimization
Laurent Condat, Adil Salim, Peter Richtarik 
On a PrimalDual Newton Proximal Method for Convex Quadratic Programs
Alberto De Marchi
Thursday, 11:00  12:40
TB02: Nonlinear Composite and Constrained Optimization  Part II
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

A primal dual method for optimization with nonlinear constraints
Mehmet Fatih Sahin 
Safe Screening for the Generalized Conditional Gradient Method
Yifan Sun 
An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints
Adil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtarik 
Larger stepsizes for some primaldual algorithms
Ming Yan, Zhi Li
Thursday, 15:15  16:30
TD02: Advances in DouglasRachford method  Part I
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

SplitDouglasRachford for composite monotone inclusions and SplitADMM
Luis BriceñoArias, Fernando Roldán 
Anderson Accelerated DouglasRachford Splitting
Anqi Fu, Junzi Zhang, Stephen Boyd 
DouglasRachford splitting and ADMM for nonconvex optimization: Accelerated and Newtontype algorithms
Lorenzo Stella, Andreas Themelis, Panagiotis Patrinos
Thursday, 16:50  18:30
TE02: Beyond Firstorder Optimization Methods for Machine Learning  Part II
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):
Fred Roosta, Albert Berahas

Fulllow evaluation type methods for derivativefree optimization
Luis Nunes Vicente, Albert Berahas, Oumaima Sohab 
Invexification of NonLinear LeastSquares Problems
Fred Roosta 
Inexact Restoration with Subsampled Trustregion methods for finitesum minimization
Stefania Bellavia, Natasa Krejic, Benedetta Morini 
Retrospective Approximation for Stochastic Optimization
Raghu Bollapragada 
Global optimization using random embeddings
Estelle Massart, Coralia Cartis, Adilet Otemissov
Friday
Friday, 9:00  10:40
FA02: Beyond Firstorder Optimization Methods for Machine Learning  Part III
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):
Fred Roosta, Albert Berahas

Largescale derivativefree optimization using subspace methods
Lindon Roberts, Coralia Cartis 
Efficient Newton Methods for Robust Stochastic Nonconvex Optimization
Thomas O'LearyRoseberry, Nick Alger, Omar Ghattas 
A stochastic second ordertype extrastep scheme for nonsmooth nonconvex optimization
Andre Milzarek, Minghan Yang, Zaiwen Wen, Tong Zhang 
Doubly Adaptive Scaled Algorithm for Machine Learning Using SecondOrder Information
Martin Takac, Majid Jahani, Sergey Rusakov, Zheng Shi, Peter Richtarik, Michael Mahoney
Friday, 11:00  12:40
FB02: Advances in DouglasRachford method  Part II
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

Shadow DouglasRachford splitting
Matthew Tam 
The Cyclic DouglasRachford Algorithm with rsetsDouglasRachford Operators
Aviv Gibali, Francisco Javier Aragón Artacho, Yair Censor 
Forwardpartial inversehalfforward splitting algorithm for solving monotone inclusions with applications
Yuchao Tang 
Multivariate Monotone Inclusions in Saddle Form
Patrick Combettes, Minh Bui
Friday, 15:15  16:30
FD02: Advances in mathematical optimization for machine learning and data analysis  Part III
Stream: Advances in mathematical optimization for machine learning
Room: Turing
Chair(s):

Mixed integer optimization in ARMA models
Leonardo Di Gangi 
Model of Optimal Centroids Approach For Multivariate Data Classification
Pham Van Nha, Le Cam Binh 
IGLOO: A stochastic global optimization algorithm to predict the structure of biomolecules adsorbed on metal surfaces
Juan CORTES, Nathalie TARRAT, Christian Schoen