Co-occurring keywords · papers mentioning both
Papers
Graphical Nonconvex Optimization via an Adaptive Convex Relaxation
ICML 2018
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods
JMLR 2018
Learning convex bounds for linear quadratic control policy synthesis
NeurIPS 2018
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity
NeurIPS 2018
Level-Set Methods for Finite-Sum Constrained Convex Optimization
ICML 2018
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
NeurIPS 2018
Lower Bounds for Higher-Order Convex Optimization
COLT 2018
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees
ICML 2018
Methods for off-line/on-line optimization under uncertainty
IJCAI 2018
Minimax Bounds on Stochastic Batched Convex Optimization
COLT 2018
Minimizing Adaptive Regret with One Gradient per Iteration
IJCAI 2018
MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization
NeurIPS 2018
Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization
JMLR 2018
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates
NeurIPS 2018
Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization
AISTATS 2018
Online Adaptive Methods, Universality and Acceleration
NeurIPS 2018
Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes
IJCAI 2018
Online Improper Learning with an Approximation Oracle
NeurIPS 2018
Online Learning of Quantum States
NeurIPS 2018
On Matching Pursuit and Coordinate Descent
ICML 2018
On the Convergence of Adam and Beyond
ICLR 2018
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
ICML 2018
PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments
CoRL 2018
Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope
ICML 2018
Provable Estimation of the Number of Blocks in Block Models
AISTATS 2018