Search Results for author:
Found 8 papers, 1 papers with code
An Accelerated Gradient Method for Simple Bilevel Optimization with Convex Lower-level Problem
In this paper, we focus on simple bilevel optimization problems, where we minimize a convex smooth objective function over the optimal solution set of another convex smooth constrained optimization problem.
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate
In this paper, we introduce a novel subspace cubic regularized Newton method that achieves a dimension-independent global convergence rate of ${O}\left(\frac{1}{mk}+\frac{1}{k^2}\right)$ for solving convex optimization problems.
Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence
Quasi-Newton algorithms are among the most popular iterative methods for solving unconstrained minimization problems, largely due to their favorable superlinear convergence property.
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems
One of the key challenges of learning an online recommendation model is the temporal domain shift, which causes the mismatch between the training and testing data distribution and hence domain generalization error.
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
To the best of our knowledge, our method achieves the best-known iteration complexity for the considered class of bilevel problems.
Generalized Optimistic Methods for Convex-Concave Saddle Point Problems
In this paper, we follow this approach and distill the underlying idea of optimism to propose a generalized optimistic method, which includes the optimistic gradient method as a special case.
Antenna Efficiency in Massive MIMO Detection
We propose a new performance metric, called antenna efficiency, to characterize how fast the vector error probability (VEP) decreases as the number of receive antennas increases in the large system limit.
Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning
To mitigate wireless fading, we further propose a cluster-based system and design the relay selection scheme based on the normalized detection SNR.
