13 citations · 44 across the 17 of their papers we have counts for
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An algorithm for minimizing convex quadratic functions over the ball
Yuyuan Ouyang
We study convex quadratic minimization over the unit ball in which the maximum eigenvalue of the Hessian matrix is bounded by a positive constant . We propose a novel firs…
Quadratic Convexification of a Square Truncated by a Hyperbola
Yipeng Zhang, Yuyuan Ouyang, Boshi Yang
We study the quadratic convexification of the compact nonconvex set which is a square truncated by…
Nonnegative Quadratics over a Quadrant with a Bilinear Constraint
Yipeng Zhang, Yuyuan Ouyang, Boshi Yang
We study quadratic polynomials that are nonnegative on the non-compact set \[ F:=\{(x_1,x_2)\in\mathbb R^2:\ x_1\ge 0,\ x_2\ge 0,\ x_1x_2\le 1\}. \] All extreme rays of the cone of…
A Note on the Gradient-Evaluation Sequence in Accelerated Gradient Methods
Yan Wu, Yipeng Zhang, Lu Liu +1
Nesterov's accelerated gradient descent method (AGD) is a seminal deterministic first-order method known to achieve the optimal order of iteration complexity for solving convex smo…
Universal and Parameter-free Gradient Sliding for Composite Optimization
Yan Wu, Yuyuan Ouyang, Zhe Zhang +1
We propose a Parameter-Free Universal Gradient Sliding (PFUGS) algorithm for computing an approximate solution to the convex composite optimization ,…
Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization
Guanghui Lan, Yuyuan Ouyang, Zhe Zhang
We propose novel optimal and parameter-free algorithms for computing an approximate solution with small (projected) gradient norm. Specifically, for computing an approximate soluti…
Mirror-prox sliding methods for solving a class of monotone variational inequalities
Guanghui Lan, Yuyuan Ouyang
In this paper we propose new algorithms for solving a class of structured monotone variational inequality (VI) problems over compact feasible sets. By identifying the gradient comp…
Universal Conditional Gradient Sliding for Convex Optimization
Yuyuan Ouyang, Trevor Squires
In this paper, we present a first-order projection-free method, namely, the universal conditional gradient sliding (UCGS) method, for solving -approximate solutions to…
Graph topology invariant gradient and sampling complexity for decentralized and stochastic optimization
Guanghui Lan, Yuyuan Ouyang, Yi Zhou
One fundamental problem in decentralized multi-agent optimization is the trade-off between gradient/sampling complexity and communication complexity. We propose new algorithms whos…
Backtracking linesearch for conditional gradient sliding
Hamid Nazari, Yuyuan Ouyang
We present a modification of the conditional gradient sliding (CGS) method that was originally developed in \cite{lan2016conditional}. While the CGS method is a theoretical breakth…
Some Worst-Case Datasets of Deterministic First-Order Methods for Solving Binary Logistic Regression
Yuyuan Ouyang, Trevor Squires
We present in this paper some worst-case datasets of deterministic first-order methods for solving large-scale binary logistic regression problems. Under the assumption that the nu…
Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems
Yuyuan Ouyang, Yangyang Xu
On solving a convex-concave bilinear saddle-point problem (SPP), there have been many works studying the complexity results of first-order methods. These results are all about uppe…
Accelerated gradient sliding for structured convex optimization
Guanghui Lan, Yuyuan Ouyang
Our main goal in this paper is to show that one can skip gradient computations for gradient descent type methods applied to certain structured convex programming (CP) problems. To…
Fast Bundle-Level Type Methods for unconstrained and ball-constrained convex optimization
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang +1
It has been shown in \cite{Lan13-1} that the accelerated prox-level (APL) method and its variant, the uniform smoothing level (USL) method, have optimal iteration complexity for so…
Accelerated Schemes For A Class of Variational Inequalities
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang
We propose a novel method, namely the accelerated mirror-prox (AMP) method, for computing the weak solutions of a class of deterministic and stochastic monotone variational inequal…
An Accelerated Linearized Alternating Direction Method of Multipliers
Yuyuan Ouyang, Yunmei Chen, Guanghui Lan +1
We present a novel framework, namely AADMM, for acceleration of linearized alternating direction method of multipliers (ADMM). The basic idea of AADMM is to incorporate a multi-ste…
Optimal Primal-Dual Methods for a Class of Saddle Point Problems
Yunmei Chen, Guanghui Lan, Yuyuan Ouyang
We present a novel accelerated primal-dual (APD) method for solving a class of deterministic and stochastic saddle point problems (SPP). The basic idea of this algorithm is to inco…