Papers
Latent Structured Active Learning
Wenjie Luo, Alex Schwing, Raquel Urtasun
Analyzing Hogwild Parallel Gaussian Gibbs Sampling
Matthew J Johnson, James Saunderson, Alan Willsky
What do row and column marginals reveal about your dataset?
Behzad Golshan, John Byers, Evimaria Terzi
Deep content-based music recommendation
Aaron van den Oord, Sander Dieleman, Benjamin Schrauwen
Reasoning With Neural Tensor Networks for Knowledge Base Completion
Richard Socher, Danqi Chen, Christopher D. Manning et al.
Designed Measurements for Vector Count Data
Liming Wang, David E Carlson, Miguel Rodrigues et al.
Flexible sampling of discrete data correlations without the marginal distributions
Alfredo Kalaitzis, Ricardo Silva
EDML for Learning Parameters in Directed and Undirected Graphical Models
Khaled S Refaat, Arthur Choi, Adnan Darwiche
Nonparametric Multi-group Membership Model for Dynamic Networks
Myunghwan Kim, Jure Leskovec
Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators.
Michel Besserve, Nikos K. Logothetis, Bernhard Schölkopf
Optimistic Concurrency Control for Distributed Unsupervised Learning
Xinghao Pan, Joseph E Gonzalez, Stefanie Jegelka et al.
Learning invariant representations and applications to face verification
Qianli Liao, Joel Z. Leibo, Tomaso Poggio
Multisensory Encoding, Decoding, and Identification
Aurel A. Lazar, Yevgeniy Slutskiy
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
Rie Johnson, Tong Zhang
Thompson Sampling for 1-Dimensional Exponential Family Bandits
Nathaniel Korda, Emilie Kaufmann, Remi Munos
Sparse Inverse Covariance Estimation with Calibration
Tuo Zhao, Han Liu
The Randomized Dependence Coefficient
David Lopez-Paz, Philipp Hennig, Bernhard Schölkopf
Convex Two-Layer Modeling
Özlem Aslan, Hao Cheng, Xinhua Zhang et al.
PAC-Bayes-Empirical-Bernstein Inequality
Ilya O Tolstikhin, Yevgeny Seldin
A Latent Source Model for Nonparametric Time Series Classification
George H Chen, Stanislav Nikolov, Devavrat Shah
Spectral methods for neural characterization using generalized quadratic models
ll Memming Park, Evan W Archer, Nicholas Priebe et al.
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions
Ari Pakman, Liam Paninski
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses
Harish G. Ramaswamy, Shivani Agarwal, Ambuj Tewari
Moment-based Uniform Deviation Bounds for k-means and Friends
Matus J Telgarsky, Sanjoy Dasgupta