Saeed Masiha

activity

20222026

most citedLearning Algorithm Generalization Error Bounds via Auxiliary Distributions

1 citations · 4 across the 9 of their papers we have counts for

collaborators

9 papers

math.OC2026

Sharp First-Order Lower Bounds under $α$ -Polyak-Lojasiewicz Conditions

Saeed Masiha, Negar Kiyavash, Patrick Thiran

We study first-order oracle complexity under the $α$ -Polyak-Lojasiewicz condition $f (x) - f_{⋆} \leq τ ∥\nabla f (x) ∥^{α}$ for $α \in [1, 2]$ . For $α < 2$ , we first show that global $L$ -sm…

math.OC2026

Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets

Saeed Masiha, Zebang Shen, Negar Kiyavash +1

We study optimistic bilevel optimization when the lower-level problem has a non-isolated manifold of minimizers. In this setting, the hyper-objective may be non-differentiable beca…

cs.GT2026

Zeroth-Order Stackelberg Control in Combinatorial Congestion Games

Saeed Masiha, Sepehr Elahi, Negar Kiyavash +1

We study Stackelberg (leader--follower) tuning of network parameters (tolls, capacities, incentives) in combinatorial congestion games, where selfish users choose discrete routes (…

math.OC2025

Superquantile-Gibbs Relaxation for Minima-selection in Bilevel Optimization

Saeed Masiha, Zebang Shen, Negar Kiyavash +1

Bilevel optimization (BLO) becomes more challenging when the lower-level objective admits multiple minimizers. Compared with the commonly studied unique-minimizer setting, this int…

math.OC2024

Optimal Local Convergence Rates of Stochastic First-Order Methods under Local $α$ -PL

Saeed Masiha, Saber Salehkaleybar, Niao He +2

We study the local convergence rate of stochastic first-order methods under a local $α$ -Polyak-Lojasiewicz ( $α$ -PL) condition in a neighborhood of a target connected component $\ma…

math.OC2022★ 1 cited

Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control

Yi Cheng, Guanghui Lan, Saeed Masiha +1

We study projection-free methods for functional constrained optimization with convex or smooth nonconvex objectives. Such problems arise in applications such as portfolio optimizat…

cs.LG2022★ 1 cited

Learning Algorithm Generalization Error Bounds via Auxiliary Distributions

Gholamali Aminian, Saeed Masiha, Laura Toni +1

Generalization error bounds are essential for comprehending how well machine learning models work. In this work, we suggest a novel method, i.e., the Auxiliary Distribution Method,…

cs.IT2022★ 1 cited

f-divergences and their applications in lossy compression and bounding generalization error

Saeed Masiha, Amin Gohari, Mohammad Hossein Yassaee

In this paper, we provide three applications for $f$ -divergences: (i) we introduce Sanov's upper bound on the tail probability of the sum of independent random variables based on s…