Papers
“Learning-Compression” Algorithms for Neural Net Pruning
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
Learning Compression from Limited Unlabeled Data
Xiangyu He, Jian Cheng
Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra
John T Halloran, David M Rocke
Learning Concept Abstractness Using Weak Supervision
Ella Rabinovich, Benjamin Sznajder, Artem Spector et al.
Learning Conceptual Space Representations of Interrelated Concepts
Zied Bouraoui, Steven Schockaert
Learning Conditional Acoustic Latent Representation with Gender and Age Attributes for Automatic Pain Level Recognition
Jeng-Lin Li, Yi-Ming Weng, Chip-Jin Ng et al.
Learning Conditioned Graph Structures for Interpretable Visual Question Answering
Will Norcliffe-Brown, Stathis Vafeias, Sarah Parisot
Learning Confidence Sets using Support Vector Machines
Wenbo Wang, Xingye Qiao
Learning Context-Sensitive Convolutional Filters for Text Processing
Dinghan Shen, Martin Renqiang Min, Yitong Li et al.
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
Maximillian Nickel, Douwe Kiela
Learning Continuous Time Bayesian Networks in Non-stationary Domains
Simone Villa, Fabio Stella
Learning convex bounds for linear quadratic control policy synthesis
Jack Umenberger, Thomas B Schön
Learning convex polytopes with margin
Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich et al.
Learning Convolutional Networks for Content-Weighted Image Compression
Mu Li, Wangmeng Zuo, Shuhang Gu et al.
Learning Data Terms for Non-blind Deblurring
Jiangxin Dong, Jinshan Pan, Deqing Sun et al.
Learning Decision Trees with Stochastic Linear Classifiers
Tom Jurgenson, Yishay Mansour
Learning Deep Descriptors With Scale-Aware Triplet Networks
Michel Keller, Zetao Chen, Fabiola Maffra et al.
Learning Deep Disentangled Embeddings With the F-Statistic Loss
Karl Ridgeway, Michael Mozer
Learning Deep Mean Field Games for Modeling Large Population Behavior
Jiachen Yang, Xiaojing Ye, Rakshit Trivedi et al.
Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
Yaojie Liu, Amin Jourabloo, Xiaoming Liu
Learning Deep Representations with Probabilistic Knowledge Transfer
Nikolaos Passalis, Anastasios Tefas
Learning Deep ResNet Blocks Sequentially using Boosting Theory
Furong Huang, Jordan Ash, John Langford et al.
Learning Deep Sketch Abstraction
Umar Riaz Muhammad, Yongxin Yang, Yi-Zhe Song et al.
Learning Deep Structured Active Contours End-to-End
Diego Marcos, Devis Tuia, Benjamin Kellenberger et al.