July 23, 2019 16:08

Abstract

Abstract

The purpose of this workshop is to bring together discrete optimizers and machine learning researchers, theory people and practitioners in an effort to bridge the fields and stimulate cross-disciplinary interaction.

Program
Monday, July 29
09h30 – 10h00 Reception/ Opening remarks
10h00 – 12h00 Session A1 Chair: Amitabh Basu
A11 An approximation algorithm for training one-node ReLU neural network/ Santanu Dey (Georgia Tech)
A12 Subspace communication driven search for high dimensional optimization/ Logan Mathesen (Arizona State University)
A13 A limiting analysis of regularization of SDP and its implication to infeasibleinterior-point algorithms/ Takashi Tsuchiya (Graduate Research Institute for Policy Studies)
A14 Stochastic proximal methods for non-smooth non-convex constrained sparseoptimization/ Michael Metel (RIKEN AIP)
12h00 – 13h00 Lunch
13h00 – 14h30 Session A2 Chair: Santanu Dey
A21 Locally accelerated conditional gradients/ Alejandro Carderera (Georgia Tech)
A22 No-regret algorithms for onlinek-submodular maximization/ Tasuku Soma (University of Tokyo)
A23 Parallel depth-first search and the applications to data mining/ Kazuki Yoshizoe (RIKEN AIP)
14h30 – 15h00 Coffee break
15h00 – 16h30 Session A3 Chair: Giulia Pedrielli
A31 Bayesian deep learning in portfolio optimization/ Akshay Gupte (Clemson University)
A32 Learning-algorithms from Bayesian principles/ Emtiyaz Khan (RIKEN AIP)
A33 Matrix co-completion for multi-label classification with missing featuresand labels/ Miao Xu (RIKEN AIP)
Tuesday, July 30
09h30 – 10h00 Reception
10h00 – 12h00 Session B1 Chair: Masashi Sugiyama
B11 Statistical decision theory perspectives on learning and stochastic optimiza-tion/ Amitabh Basu (Johns Hopkins University)
B12 On solving mixed integer non linear programs with separable non convexi-ties/ Claudia D’Ambrosio (CNRS & Ecole Polytechnique)
B13 Blended matching pursuit/ Cyrille Combettes (Georgia Tech)
B14 Simulation based mixed integer programming/ Alexander Martin (Universit ̈at Erlangen-N ̈urnberg)
12h00 – 13h00 Lunch
13h00 – 14h30 Session B2 Chair: Edwin Romeijn
B21 Strong mixed-integer programming formulations for trained neural net-works/ Joey Huchette (Massachusetts Institute of Technology)
B22 Airline schedule planning under infrastructure constraint and with customerchoice evaluation/ S ́ebastien Deschamps (Ecole Nationale des Ponts et Chauss ́ees)
B23 Adding variables – speed up by including new binary variables/ Robert Hildebrand (Virginia Tech)
14h30 – 15h00 Coffee
15h00 – 17h00 Session B3 Chair: Alexander Martin
B31 Causal-retro-causal Systems induce a dynamics on a manifold/ Hans-Georg Zimmermann (Fraunhofer N ̈urnberg)
B32 Adaptive algorithm for finding connected dominating sets in uncertaingraphs/ Takuro Fukunaga (Chuo University)
B33 Computing full conformal prediction set with approximate homotopy/ Eug`ene Ndiaye (RIKEN AIP)
B34 Differentiable ranks using optimal transport: The Sinkhorn CDF and quan-tile operator/ Marco Cuturi (Google Brain)
Wednesday, July 31
09h30 – 10h00 Reception
10h00 – 12h00 Session C1 Chair: Claudia D’Ambrosio
C11 Sampling fromlogsupermodular distribution/ Shuji Kijima (Kyushu University)
C12 Fair dimensionality reduction and iterative rounding for SDPs/ Uthaipon Tantipongpipat (Georgia Tech)
C13 Random projections for quadratic programs/ Leo Liberti (CNRS & Ecole Polytechnique)
C14 Random projection for conic programming/ Pierre-Louis Poirion (RIKEN AIP)
12h00 – 14h00 Lunch
14h00 – 15h30 Session C2 Chair: Leo Liberti
C21 Multi-armed bandit problem in piece-wise stationary environment/ Chi-Guhn Lee (University of Toronto)
C22 Policy transfer via greedy state recoding/ Christopher Mutschler (Universit ̈at Erlangen-N ̈urnberg)
C23 Stochastic monotone submodular maximization with queries/ Takanori Maehara (RIKEN AIP)
15h30 – 16h00 Coffee
16h00 – 17h30 Session C3 Chair: Joey Huchette
C31 Tensor network representation in machine learning/ Qibin Zhao (RIKEN AIP)
C32 Machine learning approaches in brain correlates of dementia elucidation -tensor machine lLearning and beyond/ Tomasz Rutkowski (University of Tokyo / RIKEN AIP)
C33 Towards robust deep learning/ Bo Han (RIKEN AIP)
17h30 Closing remarks

(Last update: July 23, 2019)

More Information

Date July 29, 2019 (Mon) 10:00 - 16:30
July 30, 2019 (Tue) 10:00 - 16:30
July 31, 2019 (Wed) 10:00 - 17:30
URL http://www.cas.mcmaster.ca/~deza/tokyo2019.html

Venue

Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan