Co-occurring keywords · papers mentioning both
Papers
Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families
NeurIPS 2024
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
AISTATS 2024
Positive Concave Deep Equilibrium Models
ICML 2024
Restricted Strong Convexity of Deep Learning Models with Smooth Activations
ICLR 2023
Learning Linear Models Using Distributed Iterative Hessian Sketching
L4DC 2022
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression
NeurIPS 2019
Hamiltonian descent for composite objectives
NeurIPS 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
ICML 2019
Sketched Iterative Algorithms for Structured Generalized Linear Models
IJCAI 2019
Theoretical guarantees for EM under misspecified Gaussian mixture models
NeurIPS 2018
Statistical and Computational Guarantees for the Baum-Welch Algorithm
JMLR 2017
Variance Reduced Stochastic Gradient Descent with Neighbors
NeurIPS 2015
Phase Retrieval using Alternating Minimization
NeurIPS 2013