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 |
