Papers
Graph Matching via Multiplicative Update Algorithm
Bo Jiang, Jin Tang, Chris Ding et al.
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu, Ankan Saha, Shaunak Chatterjee
AdaGAN: Boosting Generative Models
Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet et al.
Improved Dynamic Regret for Non-degenerate Functions
Lijun Zhang, Tianbao Yang, Jinfeng Yi et al.
Influence Maximization with ε-Almost Submodular Threshold Functions
Qiang Li, Wei Chen, Institute of Computing Xiaoming Sun et al.
Inferring Generative Model Structure with Static Analysis
Paroma Varma, Bryan D He, Payal Bajaj et al.
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
Wengong Jin, Connor Coley, Regina Barzilay et al.
PRUNE: Preserving Proximity and Global Ranking for Network Embedding
Yi-An Lai, Chin-Chi Hsu, Wen Hao Chen et al.
Random Permutation Online Isotonic Regression
Wojciech Kotlowski, Wouter M. Koolen, Alan Malek
Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays
Cesar F. Caiafa, Olaf Sporns, Andrew Saykin et al.
Unsupervised learning of object frames by dense equivariant image labelling
James Thewlis, Hakan Bilen, Andrea Vedaldi
Prototypical Networks for Few-shot Learning
Jake Snell, Kevin Swersky, Richard Zemel
Dynamic Revenue Sharing
Santiago Balseiro, Max Lin, Vahab Mirrokni et al.
Random Projection Filter Bank for Time Series Data
Amir-massoud Farahmand, Sepideh Pourazarm, Daniel Nikovski
Fitting Low-Rank Tensors in Constant Time
Kohei Hayashi, Yuichi Yoshida
On-the-fly Operation Batching in Dynamic Computation Graphs
Graham Neubig, Yoav Goldberg, Chris Dyer
Self-Supervised Intrinsic Image Decomposition
Michael Janner, Jiajun Wu, Tejas D Kulkarni et al.
Adversarial Surrogate Losses for Ordinal Regression
Rizal Fathony, Mohammad Ali Bashiri, Brian Ziebart
A graph-theoretic approach to multitasking
Noga Alon, Daniel Reichman, Igor Shinkar et al.
Minimizing a Submodular Function from Samples
Eric Balkanski, Yaron Singer
Extracting low-dimensional dynamics from multiple large-scale neural population recordings by learning to predict correlations
Marcel Nonnenmacher, Srinivas C. Turaga, Jakob H Macke
Non-Stationary Spectral Kernels
Sami Remes, Markus Heinonen, Samuel Kaski
Do Deep Neural Networks Suffer from Crowding?
Anna Volokitin, Gemma Roig, Tomaso A Poggio
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
Yingce Xia, Fei Tian, Lijun Wu et al.