Papers
4,025 papers found
Efficient Bayesian Experimental Design for Implicit Models
Steven Kleinegesse, Michael U. Gutmann
Efficient Bayesian Optimization for Target Vector Estimation
Anders Kirk Uhrenholt, Bjøern Sand Jensen
Efficient Bayes Risk Estimation for Cost-Sensitive Classification
Daniel Andrade, Yuzuru Okajima
Efficient Greedy Coordinate Descent for Composite Problems
Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich et al.
Efficient Inference in Multi-task Cox Process Models
Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla
Efficient Linear Bandits through Matrix Sketching
Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods
Aryan Mokhtari, Asuman Ozdaglar, Ali Jadbabaie
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Victor Veitch, Morgane Austern, Wenda Zhou et al.
Error bounds for sparse classifiers in high-dimensions
Antoine Dedieu
Estimating Network Structure from Incomplete Event Data
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Estimation of Non-Normalized Mixture Models
Takeru Matsuda, Aapo Hyvärinen
Evaluating model calibration in classification
Juozas Vaicenavicius, David Widmann, Carl Andersson et al.
Exploring $k$ out of Top $ρ$ Fraction of Arms in Stochastic Bandits
Wenbo Ren, Jia Liu, Ness B. Shroff
Exploring Fast and Communication-Efficient Algorithms in Large-Scale Distributed Networks
Yue Yu, Jiaxiang Wu, Junzhou Huang
Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization
Jonas Kohler, Hadi Daneshmand, Aurelien Lucchi et al.
Exponential Weights on the Hypercube in Polynomial Time
Sudeep Raja Putta, Abhishek Shetty
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models
Jiong Zhang, Parameswaran Raman, Shihao Ji et al.
Fast Algorithms for Sparse Reduced-Rank Regression
Benjamin Dubois, Jean-François Delmas, Guillaume Obozinski
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
Sharan Vaswani, Francis Bach, Mark Schmidt
Fast and Robust Shortest Paths on Manifolds Learned from Data
Georgios Arvanitidis, Soren Hauberg, Philipp Hennig et al.
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds
Pan Zhou, Xiao-Tong Yuan, Jiashi Feng
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs
Philippe Wenk, Alkis Gotovos, Stefan Bauer et al.
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems
Dan Garber, Atara Kaplan
Feature subset selection for the multinomial logit model via mixed-integer optimization
Shunsuke Kamiya, Ryuhei Miyashiro, Yuichi Takano
Finding the bandit in a graph: Sequential search-and-stop
Pierre Perrault, Vianney Perchet, Michal Valko