Papers
LaVAN: Localized and Visible Adversarial Noise
Danny Karmon, Daniel Zoran, Yoav Goldberg
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Gellert Weisz, Andras Gyorgy, Csaba Szepesvari
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations
Ashwin Kalyan, Stefan Lee, Anitha Kannan et al.
Learning Adversarially Fair and Transferable Representations
David Madras, Elliot Creager, Toniann Pitassi et al.
Learning a Mixture of Two Multinomial Logits
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins
Learning and Memorization
Satrajit Chatterjee
Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Ariel Jaffe, Roi Weiss, Boaz Nadler et al.
Learning by Playing Solving Sparse Reward Tasks from Scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe et al.
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
Maximillian Nickel, Douwe Kiela
Learning Deep ResNet Blocks Sequentially using Boosting Theory
Furong Huang, Jordan Ash, John Langford et al.
Learning Diffusion using Hyperparameters
Dimitris Kalimeris, Yaron Singer, Karthik Subbian et al.
Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius, Steve Kroon, Herman Kamper
Learning Equations for Extrapolation and Control
Subham Sahoo, Christoph Lampert, Georg Martius
Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling
Kejun Huang, Xiao Fu, Nicholas Sidiropoulos
Learning Implicit Generative Models with the Method of Learned Moments
Suman Ravuri, Shakir Mohamed, Mihaela Rosca et al.
Learning Independent Causal Mechanisms
Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla et al.
Learning in Integer Latent Variable Models with Nested Automatic Differentiation
Daniel Sheldon, Kevin Winner, Debora Sujono
Learning in Reproducing Kernel Kreı̆n Spaces
Dino Oglic, Thomas Gaertner
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations
Ting Chen, Martin Renqiang Min, Yizhou Sun
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama, Dave Zachariah, Thomas Schön
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu Trinh, Andrew Dai, Thang Luong et al.
Learning Long Term Dependencies via Fourier Recurrent Units
Jiong Zhang, Yibo Lin, Zhao Song et al.
Learning Low-Dimensional Temporal Representations
Bing Su, Ying Wu
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal, Jean Honorio