Results 11 to 20 of about 342 (117)

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua, Jie Sui, Hui Fang, Chuan Hu, Dewei Yi   +4 more
wiley   +1 more source

Minimax optimal control problems for an extensible beam equation with uncertain initial velocity

Boundary Value Problems, 2023
This paper is devoted to the problem of minimax optimal control problems of an extensible beam equation with distributed controls and initial velocity disturbances (or noises).
Jin-soo Hwang
doaj   +1 more source

Sufficient optimality condition and duality of nondifferentiable minimax ratio constraint problems under ( p , r )- ρ -( η , θ )-invexity

Control and Cybernetics, 2022
Abstract There are several classes of decision-making problems that explicitly or implicitly prompt fractional programming problems. Portfolio selection problems, agricultural planning, information transfer, numerical analysis of stochastic processes, and resource allocation problems are just a few examples.
Navdeep Kailey, Sonali Sethi, Shivani Saini   +2 more
openaire   +1 more source

Generalized Minimax Programming with Nondifferentiable (G, β)-Invexity

Journal of Applied Mathematics, 2013
We consider the generalized minimax programming problem (P) in which functions are locally Lipschitz (G, β)-invex. Not only G-sufficient but also G-necessary optimality conditions are established for problem (P ...
D. H. Yuan, X. L. Liu
doaj   +1 more source

On Nonsmooth Semi-Infinite Minimax Programming Problem with (Φ,ρ)-Invexity

Abstract and Applied Analysis, 2014
We are interested in a nonsmooth minimax programming Problem (SIP). Firstly, we establish the necessary optimality conditions theorems for Problem (SIP) when using the well-known Caratheodory's theorem.
X. L. Liu, G. M. Lai, C. Q. Xu, D. H. Yuan   +3 more
doaj   +1 more source

Convergence Analysis of Randomized SGDA under NC-PL Condition for Stochastic Minimax Optimization Problems

, 2023
We introduce a new analytic framework to analyze the convergence of the Randomized Stochastic Gradient Descent Ascent (RSGDA) algorithm for stochastic minimax optimization problems. Under the so-called NC-PL condition on one of the variables, our analysis improves the state-of-the-art convergence results in the current literature and hence broadens the
Liu, Zehua, Li, Zenan, Yuan, Xiaoming, Yao, Yuan   +3 more
openaire   +2 more sources

Maximum principle and second-order conditions for minimax problems of optimal control

Journal of Optimization Theory and Applications, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Arutyunov A.V., Silin D.B., Zerkalov L.G.   +2 more
openaire   +3 more sources

A Minimax-Program-Based Approach for Robust Fractional Multi-Objective Optimization

Mathematics
In this paper, by making use of some advanced tools from variational analysis and generalized differentiation, we establish necessary optimality conditions for a class of robust fractional minimax programming problems.
Henan Li, Zhe Hong, Do Sang Kim
doaj   +1 more source

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source