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Poster
Mon 1:00 SALD: Sign Agnostic Learning with Derivatives
Matan Atzmon, Yaron Lipman
Poster
Mon 1:00 Wasserstein-2 Generative Networks
Alexander Korotin, Vage Egiazarian, Arip Asadulaev, Alexander Safin, Evgeny Burnaev
Poster
Mon 1:00 Wasserstein Embedding for Graph Learning
Soheil Kolouri, Navid Naderializadeh, Gustavo K Rohde, Heiko Hoffmann
Poster
Mon 9:00 NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation
Angtian Wang, Adam Kortylewski, Alan Yuille
Poster
Mon 9:00 Learning Hyperbolic Representations of Topological Features
Panagiotis Kyriakis, Iordanis Fostiropoulos, Paul Bogdan
Poster
Mon 9:00 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Poster
Mon 9:00 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Poster
Mon 9:00 Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures
Pedro Hermosilla Casajus, Marco Schäfer, Matej Lang, Gloria Fackelmann, Pere-Pau Vázquez, Barbora Kozlikova, Michael Krone, Tobias Ritschel, Timo Ropinski
Poster
Mon 9:00 Primal Wasserstein Imitation Learning
Robert Dadashi, Hussenot Hussenot-Desenonges, Matthieu Geist, Olivier Pietquin
Poster
Mon 17:00 Learning a Latent Simplex in Input Sparsity Time
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David Woodruff, Samson Zhou
Poster
Mon 17:00 Improved Estimation of Concentration Under $\ell_p$-Norm Distance Metrics Using Half Spaces
Jack Prescott, XIAO ZHANG, David Evans
Spotlight
Mon 20:48 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Poster
Tue 9:00 Are wider nets better given the same number of parameters?
Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur
Poster
Tue 9:00 SSD: A Unified Framework for Self-Supervised Outlier Detection
Vikash Sehwag, Mung Chiang, Prateek Mittal
Poster
Tue 9:00 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Poster
Tue 9:00 Distance-Based Regularisation of Deep Networks for Fine-Tuning
Henry Gouk, Timothy Hospedales, massimiliano pontil
Poster
Tue 17:00 Dataset Inference: Ownership Resolution in Machine Learning
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot
Spotlight
Tue 19:35 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Spotlight
Tue 21:53 Neural Topic Model via Optimal Transport
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine
Poster
Wed 1:00 New Bounds For Distributed Mean Estimation and Variance Reduction
Peter Davies, Vijaykrishna Gurunathan, Niusha Moshrefi, Saleh Ashkboos, Dan Alistarh
Poster
Wed 1:00 No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet Dokania, Vineet Gandhi
Poster
Wed 1:00 Deep Learning meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
Poster
Wed 1:00 Graph Edit Networks
Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara E Hammer
Poster
Wed 1:00 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Poster
Wed 1:00 FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization
Lanqing Li, Rui Yang, Dijun Luo
Poster
Wed 9:00 Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw, ssingla Singla, Soheil Feizi
Poster
Wed 9:00 Multiplicative Filter Networks
Rizal Fathony, Anit Kumar Sahu, Devin Willmott, Zico Kolter
Poster
Wed 9:00 Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto, Philipp Becker, Vien A Ngo, Hanna Ziesche, Gerhard Neumann
Poster
Wed 9:00 Faster Binary Embeddings for Preserving Euclidean Distances
Jinjie Zhang, Rayan Saab
Oral
Wed 11:30 Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan T McAllister, Roberto Calandra, Yarin Gal, Sergey Levine
Poster
Wed 17:00 Is Attention Better Than Matrix Decomposition?
Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin
Poster
Wed 17:00 Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R Varshney
Poster
Wed 17:00 Model-Based Visual Planning with Self-Supervised Functional Distances
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Ben Eysenbach, Chelsea Finn, Sergey Levine
Poster
Thu 1:00 Learning Neural Generative Dynamics for Molecular Conformation Generation
Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
Poster
Thu 1:00 R-GAP: Recursive Gradient Attack on Privacy
Junyi Zhu, Matthew Blaschko
Poster
Thu 1:00 Neural Topic Model via Optimal Transport
He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine
Spotlight
Thu 3:35 Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
Poster
Thu 9:00 Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Ioannis Mitliagkas, Remi Combes
Poster
Thu 9:00 On Position Embeddings in BERT
Wang Benyou, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, Jakob Simonsen
Poster
Thu 9:00 Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee
Spotlight
Thu 13:50 Disentangled Recurrent Wasserstein Autoencoder
Jun Han, Martin Min, Ligong Han, Li Erran Li, Xuan Zhang
Poster
Thu 17:00 Multi-timescale Representation Learning in LSTM Language Models
Shivangi Mahto, Vy Vo, Javier Turek, Alexander Huth
Poster
Thu 17:00 Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
Spotlight
Thu 20:58 Learning a Latent Simplex in Input Sparsity Time
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David Woodruff, Samson Zhou
Spotlight
Thu 21:28 Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
Workshop
Fri 6:10 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang