Papers
Large Scale Distributed Deep Networks
Jeffrey Dean, Greg Corrado, Rajat Monga et al.
Large-scale Linear Support Vector Regression
Chia-Hua Ho, Chih-Jen Lin
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning
Matthew Der, Lawrence K. Saul
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs
Anima Anandkumar, Ragupathyraj Valluvan
Learned Prioritization for Trading Off Accuracy and Speed
Jiarong Jiang, Adam Teichert, Jason Eisner et al.
Learning about Canonical Views from Internet Image Collections
Elad Mezuman, Yair Weiss
Learning Algorithms for the Classification Restricted Boltzmann Machine
Hugo Larochelle, Michael Mandel, Razvan Pascanu et al.
Learning and Model-Checking Networks of I/O Automata
Hua Mao, Manfred Jaeger
Learning as MAP Inference in Discrete Graphical Models
Xianghang Liu, James Petterson, Tibério S. Caetano
Learning curves for multi-task Gaussian process regression
Peter Sollich, Simon Ashton
Learning DNF Expressions from Fourier Spectrum
Vitaly Feldman
Learning Fourier Sparse Set Functions
Peter Stobbe, Andreas Krause
Learning from Distributions via Support Measure Machines
Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo et al.
Learning From Ordered Sets and Applications in Collaborative Ranking
Truyen Tran, Dinh Phung, Svetha Venkatesh
Learning from the Wisdom of Crowds by Minimax Entropy
Dengyong Zhou, Sumit Basu, Yi Mao et al.
Learning from Weak Teachers
Ruth Urner, Shai Ben David, Ohad Shamir
Learning Functions of Halfspaces Using Prefix Covers
Parikshit Gopalan, Adam R. Klivans, Raghu Meka
Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs
Aharon Birnbaum, Shai S. Shwartz
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
Learning Image Descriptors with the Boosting-Trick
Tomasz Trzcinski, Mario Christoudias, Vincent Lepetit et al.
Learning Invariant Representations of Molecules for Atomization Energy Prediction
Grégoire Montavon, Katja Hansen, Siamac Fazli et al.
Learning Label Trees for Probabilistic Modelling of Implicit Feedback
Andriy Mnih, Yee W. Teh
Learning Latent Variable Models by Pairwise Cluster Comparison
Nuaman Asbeh, Boaz Lerner
Learning Linear Cyclic Causal Models with Latent Variables
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoyer
Learning Low-order Models for Enforcing High-order Statistics
Patrick Pletscher, Pushmeet Kohli