Papers
Kernel Mean Matching for Content Addressability of GANs
Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal et al.
Kernel Normalized Cut: a Theoretical Revisit
Yoshikazu Terada, Michio Yamamoto
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection
Lotfi Slim, Clément Chatelain, Chloe-Agathe Azencott et al.
Ladder Capsule Network
Taewon Jeong, Youngmin Lee, Heeyoung Kim
Large-Scale Sparse Kernel Canonical Correlation Analysis
Viivi Uurtio, Sahely Bhadra, Juho Rousu
LatentGNN: Learning Efficient Non-local Relations for Visual Recognition
Songyang Zhang, Xuming He, Shipeng Yan
Latent Normalizing Flows for Discrete Sequences
Zachary Ziegler, Alexander Rush
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
Shanshan Wu, Alex Dimakis, Sujay Sanghavi et al.
Learning Action Representations for Reinforcement Learning
Yash Chandak, Georgios Theocharous, James Kostas et al.
Learning and Data Selection in Big Datasets
Hossein Shokri Ghadikolaei, Hadi Ghauch, Carlo Fischione et al.
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
Kelvin Xu, Ellis Ratner, Anca Dragan et al.
Learning Classifiers for Target Domain with Limited or No Labels
Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
Learning Context-dependent Label Permutations for Multi-label Classification
Jinseok Nam, Young-Bum Kim, Eneldo Loza Mencia et al.
Learning deep kernels for exponential family densities
Li Wenliang, Danica J. Sutherland, Heiko Strathmann et al.
Learning Dependency Structures for Weak Supervision Models
Paroma Varma, Frederic Sala, Ann He et al.
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
Yeonwoo Jeong, Hyun Oh Song
Learning Discrete Structures for Graph Neural Networks
Luca Franceschi, Mathias Niepert, Massimiliano Pontil et al.
Learning Distance for Sequences by Learning a Ground Metric
Bing Su, Ying Wu
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
Tri Dao, Albert Gu, Matthew Eichhorn et al.
Learning from a Learner
Alexis Jacq, Matthieu Geist, Ana Paiva et al.
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
Timothy Arthur Mann, Sven Gowal, Andras Gyorgy et al.
Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause et al.
Learning Hawkes Processes Under Synchronization Noise
William Trouleau, Jalal Etesami, Matthias Grossglauser et al.
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker, Gergo Bohner, Julien Boussard et al.
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer et al.