Papers
4,025 papers found
Adaptive Variable Clustering in Gaussian Graphical Models
Siqi Sun, Yuancheng Zhu, Jinbo Xu
A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models
Ruitong Huang, Csaba Szepesvari
A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data
Do-kyum Kim, Matthew Der, Lawrence Saul
A Geometric Algorithm for Scalable Multiple Kernel Learning
John Moeller, Parasaran Raman, Suresh Venkatasubramanian et al.
A Level-set Hit-and-run Sampler for Quasi-Concave Distributions
Shane Jensen, Dean Foster
Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold
Franz Király, Martin Ehler
Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?
Shinichi Nakajima, Masashi Sugiyama
Analytic Long-Term Forecasting with Periodic Gaussian Processes
Nooshin HajiGhassemi, Marc Deisenroth
An Analysis of Active Learning with Uniform Feature Noise
Aaditya Ramdas, Barnabas Poczos, Aarti Singh et al.
An Efficient Algorithm for Large Scale Compressive Feature Learning
Hristo Paskov, John Mitchell, Trevor Hastie
A New Approach to Probabilistic Programming Inference
Frank Wood, Jan Willem Meent, Vikash Mansinghka
A New Perspective on Learning Linear Separators with Large L_qL_p Margins
Maria-Florina Balcan, Christopher Berlind
An inclusion optimal algorithm for chain graph structure learning
Jose Peña, Dag Sonntag, Jens Nielsen
An LP for Sequential Learning Under Budgets
Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama
A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response
Ava Bargi, Richard Yi Xu, Zoubin Ghahramani et al.
Approximate Slice Sampling for Bayesian Posterior Inference
Christopher DuBois, Anoop Korattikara, Max Welling et al.
A Statistical Model for Event Sequence Data
Kevin Heins, Hal Stern
Average Case Analysis of High-Dimensional Block-Sparse Recovery and Regression for Arbitrary Designs
Waheed Bajwa, Marco Duarte, Robert Calderbank
Avoiding pathologies in very deep networks
David Duvenaud, Oren Rippel, Ryan Adams et al.
Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel
Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate Jones et al.
Bayesian Logistic Gaussian Process Models for Dynamic Networks
Daniele Durante, David Dunson
Bayesian Multi-Scale Optimistic Optimization
Ziyu Wang, Babak Shakibi, Lin Jin et al.
Bayesian Nonparametric Poisson Factorization for Recommendation Systems
Prem Gopalan, Francisco J. Ruiz, Rajesh Ranganath et al.
Bayesian Switching Interaction Analysis Under Uncertainty
Zoran Dzunic, John Fisher III