Oral Presentations

• High Dimensional Gaussian Graphical Model on Network-linked Data. Tianxi Li, Cheng Qian, Liza Levina, Ji Zhu.
• Edge Exchangeable Temporal Network Models. Yin Cheng Ng, Ricardo Silva.
• Estimating Mixed Memberships with Sharp Eigenvector Deviations. Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti.
• Learning High-Dimensional DAGs: Provable Statistical Guarantees and Scalable Approximation. Bryon Aragam, Jiaying Gu, Arash Amini, Qing Zhou.
• The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities. Arun Sai Suggala, Mladen Kolar, Pradeep Ravikumar.
• A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks. Farshad Harirchi.

Poster Presentations

• Phase Transitions in Image Denoising via Sparsely Coding Convolutional Neural Networks. Jacob A Carroll, Garrett T Kenyon, Nils Carlson.
• Medoids in Almost Linear Time via Multi-Armed Bandits. Vivek Bagaria, Govinda M Kamath, Vasilis Ntranos, Martin Zhang, David Tse.
• A Streaming Algorithm for Graph Clustering. Alexandre Hollocou, Thomas Bonald, Marc Lelarge.
• Double Articulation Approach for Segmentation of Human Interaction using BP-AR-HMM and NPYLM. Jeric C Briones, Takatomi Kubo, Kazushi Ikeda.
• Sparse Diffusion-Convolutional Neural Networks. James Atwood, Siddharth Pal, Don Towsley, Ananthram Swami.
• Biomarker discovery via integrative analysis of longitudinal metabolic data. Takoua Jendoubi.
• Predicting Growth Rate from in silico Models. John W Santerre.
• Sparse exponential family graphical models for multivariate circular data. Natalie Klein, Josue Orellana.
• Trend Filtering in Network Time Series with Applications to Traffic Incident Detection. Pranamesh Chakraborty, Chinmay Hegde, Anuj Sharma.
• Community Detection in Bipartite Networks with Node Covariates. Zahra Razaee, Arash Amini, Jingyi Jessica Li
• Active Link Inference for Case Building Investigation. Reihaneh Rabbany, David Bayani, Artur Dubrawski.
• A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs. Chandan Singh, Yanjun Qi, Beilun Wang
• Communication-Avoiding Optimization Methods for Massive-Scale Graphical Model Structure Learning. Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluc, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine Yelick.
• Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. Beilun Wang, Arshdeep Sekhon, Yanjun Qi.
• Latent Structure Learning using Gaussian and Dirichlet Processes. Andrew Lawrence, Carl Henrik Henrik, Neill Campbell.
• Graphite: Iterative Generative Modeling of Graphs. Aditya Grover, Aaron Zweig, Stefano Ermon.
• Social Network Analysis using Coordinate Games. Radhika Arava.
• New Algorithms for Inference in Graph Sequence Models. Mehrnaz Amjadi, Theja Tulabandhula.