Saeed Ghadimi | DeepAI

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∙ 07/11/2023

Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning

We develop and analyze stochastic approximation algorithms for solving n...

0 Xuxing Chen, et al. ∙

∙ 04/21/2023

Learn What NOT to Learn: Towards Generative Safety in Chatbots

Conversational models that are generative and open-domain are particular...

0 Leila Khalatbari, et al. ∙

∙ 02/20/2023

A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization

We focus on decentralized stochastic non-convex optimization, where n ag...

0 Tesi Xiao, et al. ∙

∙ 06/22/2022

Projection-free Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data

We study a projection-free conditional gradient-type algorithm for const...

0 Abhishek Roy, et al. ∙

∙ 05/26/2022

RIGID: Robust Linear Regression with Missing Data

We present a robust framework to perform linear regression with missing ...

0 Alireza Aghasi, et al. ∙

∙ 02/09/2022

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization

We propose a projection-free conditional gradient-type algorithm for smo...

0 Tesi Xiao, et al. ∙

∙ 01/01/2022

The Parametric Cost Function Approximation: A new approach for multistage stochastic programming

The most common approaches for solving multistage stochastic programming...

0 Warren B. Powell, et al. ∙

∙ 09/28/2020

Escaping Saddle-Points Faster under Interpolation-like Conditions

In this paper, we show that under over-parametrization several standard ...

0 Abhishek Roy, et al. ∙

∙ 08/24/2020

Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates

In this paper, we study smooth stochastic multi-level composition optimi...

0 Krishnakumar Balasubramanian, et al. ∙

∙ 06/15/2020

Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions

We analyze stochastic conditional gradient type methods for constrained ...

0 Tesi Xiao, et al. ∙

∙ 07/31/2019

Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization

Bandit algorithms have been predominantly analyzed in the convex setting...

0 Abhishek Roy, et al. ∙

∙ 02/04/2019

Non-asymptotic Results for Langevin Monte Carlo: Coordinate-wise and Black-box Sampling

Euler-Maruyama and Ozaki discretization of a continuous time diffusion p...

0 Lingqing Shen, et al. ∙

∙ 09/17/2018

Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates

In this paper, we propose and analyze zeroth-order stochastic approximat...

0 Krishnakumar Balasubramanian, et al. ∙

∙ 08/29/2015

Generalized Uniformly Optimal Methods for Nonlinear Programming

In this paper, we present a generic framework to extend existing uniform...

0 Saeed Ghadimi, et al. ∙

∙ 09/22/2013

Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming

In this paper, we introduce a new stochastic approximation (SA) type alg...

0 Saeed Ghadimi, et al. ∙

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