Mo-PM2-4: Big Data Analytics |
| Session Type: Lecture |
| Time: Monday, June 15, 16:40 - 18:20 |
| Location: S426 (L4) |
| Session Chair: Andreas Host-Madsen, University of Hawaii |
| Mo-PM2-4.1: A Spectrum Decomposition to the Feature Spaces and the Application to Big Data Analytics |
| Shao-Lun Huang; Massachusetts Institute of Technology |
| Lizhong Zheng; Massachusetts Institute of Technology |
| Mo-PM2-4.2: Atypical Information Theory for Real-Valued Data |
| Anders Host-Madsen; University of Hawaii |
| Elyas Sabeti; University of Hawaii |
| Mo-PM2-4.3: Online Denoising of Discrete Noisy Data |
| Pejman Khadivi; Virginia Tech |
| Ravi Tandon; Virginia Tech |
| Naren Ramakrishnan; Virginia Tech |
| Mo-PM2-4.4: A Scalable Framework to Transform Samples from One Continuous Distribution to Another |
| Diego Mesa; University of California: San Diego |
| Sanggyun Kim; University of California: San Diego |
| Todd Coleman; University of California: San Diego |
| Mo-PM2-4.5: Efficient Total Probability Prediction via Convex Optimization and Optimal Transport |
| Sanggyun Kim; University of California, San Diego |
| Diego Mesa; University of California, San Diego |
| Todd Coleman; University of California, San Diego |
