Schedule

8:45am - 9:00am: Opening remarks

9:00am-9:45am: Invited Talk - Stefanie Jegelka

9:45am-10:30am: Coffee Break + Poster Session 1

10:30am-11:15am: Invited Talk - Siamak Ravanbakhsh

11:15am-11:30am: Contributed Talk - Towards deep amortized clustering. Juho Lee, Yoonho Lee, Yee Whye Teh

11:30am - 11:45 pm: Contributed Talk - Fair Hierarchical Clustering. Sara Ahmadian, Alessandro Epasto, Marina L Knittel, Ravi Kumar, Mohammad Mahdian, Philip Pham

11:45am-12:30pm: Invited Talk -Abhishek Khetan

12:30pm-2pm: Lunch

2:00pm - 2:30pm: Contributed Talk - Limitations of Deep Learning on Point Clouds. Christian Bueno, Alan G. Hylton.

2:00pm - 2:30pm: Contributed Talk - Chirality Nets: Exploiting Structure in Human Pose Regression. Raymond Yeh, Yuan-Ting Hu, Alex Schwing

2:30pm-3:15pm: Invited Talk - Eunsu Kang

3:15pm-4:15pm: Coffee + Poster Session 2

4:15pm-5:00pm: Invited Talk - Amr Ahmed

5:00pm-5:40pm: Panel Discussion

5:40pm-5:45pm: Brief closing remarks

Poster Session 1 (9:45AM - 10:30AM):

  • Deep Set Prediction Networks. Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
  • Deep Hyperedges: a Framework for Transductive and Inductive Learning on Hypergraphs. Joshua Payne
  • FSPool: Learning Set Representations with Featurewise Sort Pooling. Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
  • Deep Learning Features Through Dictionary Learning with Improved Clustering for Image Classification. Shengda Luo, Alex Po Leung, Haici Zhang
  • Globally Optimal Model-based Clustering via Mixed Integer Nonlinear Programming. Patrick Flaherty, Pitchaya Wiratchotisatian, Andrew C. Trapp
  • Sliding Window Algorithms for k-Clustering Problems. Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitski, Morteza Zadimoghaddam
  • Optimized Recommendations When Customers Select Multiple Products. Prasoon Patidar, Deeksha Sinha, Theja Tulabandhula
  • Manipulating Person Videos with Natural Language. Levent Karacan, Mehmet Gunel, Aykut Erdem, Erkut Erdem
  • Permutation Invariance and Relational Reasoning in Multi-Object Tracking. Fabian B. Fuchs, Adam R. Kosiorek, Li Sun, Oiwi Parker Jones, Ingmar Posner.
  • Clustering by Learning to Optimize Normalized Cuts. Azade Nazi, Will Hang, Anna Goldie, Sujith Ravi, Azalia Mirhoseini
  • Deformable Filter Convolution for Point Cloud Reasoning. Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun
  • Learning Embeddings from Cancer Mutation Sets for Classification Tasks. Geoffroy Dubourg-Felonneau, Yasmeen Kussad, Dominic Kirkham, John Cassidy, Harry W Clifford
  • Exchangeable Generative Models with Flow Scans. Christopher M. Bender, Kevin O'Connor, Yang Li, Juan Jose Garcia, Manzil Zaheer, Junier Oliva
  • Conditional Invertible Flow for Point Cloud Generation. Stypulkowski Michal, Zamorski Maciej, Zieba Maciej, Chorowski Jan
  • Getting Topology and Point Cloud Generation to Mesh. Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang
  • Distributed Balanced Partitioning and Applications in Large-scale Load Balancing. Aaron Archer, Kevin Aydin, MohammadHossein Bateni, Vahab Mirrokni, Aaron Schild, Ray Yang, Richard Zhuang

Poster Session 2 (3:15PM - 4:15PM):

  • Towards deep amortized clustering. Juho Lee, Yoonho Lee, Yee Whye Teh
  • Chirality Nets: Exploiting Structure in Human Pose Regression. Raymond Yeh, Yuan-Ting Hu, Alexander Schwing
  • Fair Hierarchical Clustering. Sara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar, Mohammad Mahdian, Philip Pham
  • Limitations of Deep Learning on Point Clouds. Christian Bueno, Alan G. Hylton
  • How Powerful Are Randomly Initialized Pointcloud Set Functions? Aditya Sanghi, Pradeep Kumar Jayaraman
  • On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets. Ignacio Arroyo-Fernández, Mauricio Carrasco-Ruiz, José Anibal Arias-Aguilar
  • Modelling Convolution as a Finite Set of Operations Through Transformation Semigroup Theory. Andrew Hryniowski, Alexander Wong
  • HCA-DBSCAN: HyperCube Accelerated Density Based Spatial Clustering for Applications with Noise. Vinayak Mathur, Jinesh Mehta, Sanjay Singh
  • Finding densest subgraph in probabilistically evolving graphs. Sara Ahmadian, Shahrzad Haddadan
  • Representation Learning with Multisets. Vasco Portilheiro
  • PairNets: Novel Fast Shallow Artificial Neural Networks on Partitioned Subspaces. Luna Zhang
  • Fair Correlation Clustering. Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian
  • Learning Maximally Predictive Prototypes in Multiple Instance Learning. Mert Yuksekgonul, Ozgur Emre Sivrikaya, Mustafa Gokce Baydogan
  • Deep Clustering using MMD Variational Autoencoder and Traditional Clustering Algorithms. Jhosimar Arias
  • Hypergraph Partitioning using Tensor Eigenvalue Decomposition. Deepak Maurya, Balaraman Ravindran, Shankar Narasimhan
  • Information Geometric Set Embeddings: From Sets to Distributions. Ke Sun, Frank Nielsen
  • Document Representations using Fine-Grained Topics. Justin Payan, Andrew McCallum