Papers
176,624 papers found
Inductive Principles for Restricted Boltzmann Machine Learning
Benjamin Marlin, Kevin Swersky, Bo Chen et al.
Inductive Regularized Learning of Kernel Functions
Prateek Jain, Brian Kulis, Inderjit S. Dhillon
Inference and communication in the game of Password
Yang Xu, Charles Kemp
Inference and Learning in Networks of Queues
Charles Sutton, Michael I. Jordan
Inference with Multivariate Heavy-Tails in Linear Models
Danny Bickson, Carlos Guestrin
Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics
Kanaka Rajan, L Abbott, Haim Sompolinsky
Infinite Predictor Subspace Models for Multitask Learning
Piyush Rai, Hal Daumé III
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski et al.
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization
Jarkko Venna, Jaakko Peltonen, Kristian Nybo et al.
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
Nguyen Xuan Vinh, Julien Epps, James Bailey
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks
Dirk Husmeier, Frank Dondelinger, Sophie Lebre
Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains
Martha White, Adam White
Introduction to Causal Inference
Peter Spirtes
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang et al.
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
Eric Wang, Dehong Liu, Jorge Silva et al.
Joint Cascade Optimization Using A Product Of Boosted Classifiers
Leonidas Lefakis, Francois Fleuret
Kernel Descriptors for Visual Recognition
Liefeng Bo, Xiaofeng Ren, Dieter Fox
Kernel Partial Least Squares is Universally Consistent
Gilles Blanchard, Nicole Krämer
Kronecker Graphs: An Approach to Modeling Networks
Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg et al.
Label Embedding Trees for Large Multi-Class Tasks
Samy Bengio, Jason Weston, David Grangier
Large Margin Learning of Upstream Scene Understanding Models
Jun Zhu, Li-jia Li, Li Fei-fei et al.
Large Margin Multi-Task Metric Learning
Shibin Parameswaran, Kilian Q. Weinberger
Large-Scale Matrix Factorization with Missing Data under Additional Constraints
Kaushik Mitra, Sameer Sheorey, Rama Chellappa
Large Scale Online Learning of Image Similarity Through Ranking
Gal Chechik, Varun Sharma, Uri Shalit et al.