2019/7/23 16:08

要旨

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)

詳細情報

日時 2019/07/29(月) 10:00 - 16:30
2019/07/30(火) 10:00 - 16:30
2019/07/31(水) 10:00 - 17:30
URL http://www.cas.mcmaster.ca/~deza/tokyo2019.html

場所

〒103-0027 東京都中央区日本橋1-4-1 日本橋一丁目三井ビルディング 15階(Google Maps)