2 citations · 4 across the 5 of their papers we have counts for
5 papers
Nonasymptotic Analysis of Accelerated Methods With Inexact Oracle Under Absolute Error Bound
Yin Liu, Sam Davanloo Tajbakhsh
Performance analysis of first-order algorithms with inexact oracles has gained recent attention due to various emerging applications in which obtaining exact gradients is impossibl…
Stochastic Optimization Algorithms for Problems with Controllable Biased Oracles
Yin Liu, Sam Davanloo Tajbakhsh
Motivated by emerging applications in machine learning, we consider an optimization problem in a general setting in which the gradient of the objective function is available via a…
Stochastic Composition Optimization of Functions without Lipschitz Continuous Gradient
Yin Liu, Sam Davanloo Tajbakhsh
In this paper, we study stochastic optimization of two-level composition of functions without Lipschitz continuous gradient. The smoothness property is generalized by the notion of…
Fitting ARMA Time Series Models without Identification: A Proximal Approach
Yin Liu, Sam Davanloo Tajbakhsh
Fitting autoregressive moving average (ARMA) time series models requires model identification before parameter estimation. Model identification involves determining the order of th…
A first-order optimization algorithm for statistical learning with hierarchical sparsity structure
Dewei Zhang, Yin Liu, Sam Davanloo Tajbakhsh
In many statistical learning problems, it is desired that the optimal solution conforms to an a priori known sparsity structure represented by a directed acyclic graph. Inducing su…