Papers
173,579 papers found
Iterative Reweighted Algorithms for Matrix Rank Minimization
Karthik Mohan, Maryam Fazel
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
Benjamin Rolfs, Bala Rajaratnam, Dominique Guillot et al.
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
Antoine Bordes, Xavier Glorot, Jason Weston et al.
Joint Modeling of a Matrix with Associated Text via Latent Binary Features
Xianxing Zhang, Lawrence Carin
Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences
Jan Grau, Jens Keilwagen, André Gohr et al.
Kernel Hyperalignment
Alexander Lorbert, Peter J. Ramadge
Kernel Latent SVM for Visual Recognition
Weilong Yang, Yang Wang, Arash Vahdat et al.
Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems
Magalie Fromont, Béatrice Laurent, Matthieu Lerasle et al.
Kernel Topic Models
Philipp Hennig, David Stern, Ralf Herbrich et al.
Key Instance Detection in Multi-Instance Learning
Guoqing Liu, Jianxin Wu, Zhi-Hua Zhou
Krylov Subspace Descent for Deep Learning
Oriol Vinyals, Daniel Povey
L1 Covering Numbers for Uniformly Bounded Convex Functions
Adityanand Guntuboyina, Bodhisattva Sen
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models
Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman et al.
Large-Margin Learning of Submodular Summarization Models
Ruben Sipos, Pannaga Shivaswamy, Thorsten Joachims
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