Papers
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm, Yung-Kyun Noh
Kernelized Synaptic Weight Matrices
Lorenz Muller, Julien Martel, Giacomo Indiveri
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki et al.
K-means clustering using random matrix sparsification
Kaushik Sinha
Knowledge Transfer with Jacobian Matching
Suraj Srinivas, Francois Fleuret
Kronecker Recurrent Units
Cijo Jose, Moustapha Cisse, Francois Fleuret
Large-Scale Cox Process Inference using Variational Fourier Features
ST John, James Hensman
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang, Salar Fattahi, Somayeh Sojoudi
Latent Space Policies for Hierarchical Reinforcement Learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel et al.
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