Poster Sessions

Full schedule: https://www.sets.parts/schedule

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
Finding densest subgraph in probabilistically evolving graphs. Sara Ahmadian, Shahrzad Haddadan

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
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

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