Papers
Emergence of Object-Selective Features in Unsupervised Feature Learning
Adam Coates, Andrej Karpathy, Andrew Y. Ng
Ensemble weighted kernel estimators for multivariate entropy estimation
Kumar Sricharan, Alfred O. Hero
Entangled Monte Carlo
Seong-hwan Jun, Liangliang Wang, Alexandre Bouchard-côté
Entropy Estimations Using Correlated Symmetric Stable Random Projections
Ping Li, Cun-hui Zhang
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization
Demba Ba, Behtash Babadi, Patrick Purdon et al.
Expectation Propagation in Gaussian Process Dynamical Systems
Marc Deisenroth, Shakir Mohamed
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress
Manuel Lopes, Tobias Lang, Marc Toussaint et al.
Exponential Concentration for Mutual Information Estimation with Application to Forests
Han Liu, Larry Wasserman, John D. Lafferty
Factorial LDA: Sparse Multi-Dimensional Text Models
Michael Paul, Mark Dredze
Factoring nonnegative matrices with linear programs
Ben Recht, Christopher Re, Joel Tropp et al.
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression
Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
FastEx: Hash Clustering with Exponential Families
Amr Ahmed, Sujith Ravi, Alex J. Smola et al.
Fast Resampling Weighted v-Statistics
Chunxiao Zhou, Jiseong Park, Yun Fu
Fast Variational Inference in the Conjugate Exponential Family
James Hensman, Magnus Rattray, Neil D. Lawrence
Feature-aware Label Space Dimension Reduction for Multi-label Classification
Yao-nan Chen, Hsuan-tien Lin
Feature Clustering for Accelerating Parallel Coordinate Descent
Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar et al.
Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling
Antonino Freno, Mikaela Keller, Marc Tommasi
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery
Ehsan Elhamifar, Guillermo Sapiro, René Vidal
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
Andre Wibisono, Martin J. Wainwright, Michael I. Jordan et al.
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach
Dijun Luo, Heng Huang, Feiping Nie et al.
Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models
Kei Wakabayashi, Takao Miura
From Deformations to Parts: Motion-based Segmentation of 3D Objects
Soumya Ghosh, Matthew Loper, Erik B. Sudderth et al.
Fully Bayesian inference for neural models with negative-binomial spiking
Jonathan W. Pillow, James Scott
Fused sparsity and robust estimation for linear models with unknown variance
Arnak Dalalyan, Yin Chen