Papers
Identifying graph-structured activation patterns in networks
James Sharpnack, Aarti Singh
Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
Zeeshan Syed, John V. Guttag
Implicit Differentiation by Perturbation
Justin Domke
Implicit encoding of prior probabilities in optimal neural populations
Deep Ganguli, Eero P. Simoncelli
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
Mathieu Salzmann, Raquel Urtasun
Improvements to the Sequence Memoizer
Jan Gasthaus, Yee W. Teh
Improving Human Judgments by Decontaminating Sequential Dependencies
Michael Mozer, Harold Pashler, Matthew Wilder et al.
Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices
Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez
Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles
Kaiming Li, Lei Guo, Carlos Faraco 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 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 Relational Modeling of Functional Connectivity in Resting State fMRI
Morten Mørup, Kristoffer Madsen, Anne-marie Dogonowski et al.
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
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
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
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho et al.
Layered image motion with explicit occlusions, temporal consistency, and depth ordering
Deqing Sun, Erik B. Sudderth, Michael J. Black