Results 71 to 80 of about 29,664 (291)

Profit Maximization for Online Advertising Demand-Side Platforms

, 2017
We develop an optimization model and corresponding algorithm for the management of a demand-side platform (DSP), whereby the DSP aims to maximize its own profit while acquiring valuable impressions for its advertiser clients.
Grigas, Paul, Lee, Kuang-chih, Lobos, Alfonso, Wen, Zheng   +3 more
core   +1 more source

Dynamic Shifts in ER–Plasma Membrane Junctions Signaling Define Pro‐Metastatic N‐Glycosylation and Predict Prostate Cancer Progression

Advanced Science, EarlyView.
Prostate cancer remains a leading cause of male cancer death, yet screening cannot reliably identify aggressive disease, underscoring the need for tissue biomarkers. It is shown that primary tumors increase ER–plasma membrane junction signaling via STIM1/ORP5, whereas metastasis features their loss, Golgi dispersal, and rapid conversion of high‐mannose
Amanda J. Macke, Tania Kamal, Taylor E. Divita, Artem N. Pachikov, Chad A. LaGrange, Rajesh Ravichandran, Martha Morton, Robert Powers, Haowen Qiu, Jean‐Jack M. Riethoven, Colm Morrissey, Melinda Wojtkiewicz, Rebekah L. Gundry, Carol A. Casey, Armen Petrosyan   +14 more
wiley   +1 more source

A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization

EURO Journal on Computational Optimization, 2021
Bilevel optimization is a field of mathematical programming in which some variables are constrained to be the solution of another optimization problem. As a consequence, bilevel optimization is able to model hierarchical decision processes.
Thomas Kleinert, Martine Labbé, Ivana Ljubić, Martin Schmidt   +3 more
doaj   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement

Journal of Economy and Technology
This paper explores algorithmic collusion from both legal and economic perspectives, underscoring the increasing influence of algorithms in firms’ market decisions and their potential to facilitate anti-competitive behaviour.
Frédéric Marty, Thierry Warin
doaj   +1 more source

Optimization Approaches for Demand-Side Management in the Smart Grid: A Systematic Mapping Study

Smart Cities, 2023
Demand-side management in the smart grid often consists of optimizing energy-related objective functions, with respect to variables, in the presence of constraints expressing electrical consumption habits.
Safaa Mimi, Yann Ben Maissa, Ahmed Tamtaoui   +2 more
doaj   +1 more source

Hierarchical Reconfigurable Metasurface Based on Scenario‐Guided Functional Modules and Programmable Core

Advanced Science, EarlyView.
This paper proposes a hierarchical reconfigurable metasurface architecture (HRMA) to achieve comprehensive electromagnetic parameter modulation and on‐demand polymorphic function switching. The reconfigurable metasurface is divided into a programmable core (PC) and scenario‐guided functional modules (FMs), exhibiting significant flexibility and ...
Lihao Zhu, Jiaqi Han, Zhe Zheng, Qiang Feng, Dexiao Xia, Xiangjin Ma, Yajie Mu, Guoliang Luo, Rui Li, Haixia Liu, Hao Xue, Long Li   +11 more
wiley   +1 more source

From Black-Scholes to Online Learning: Dynamic Hedging under Adversarial Environments [PDF]

, 2014
We consider a non-stochastic online learning approach to price financial options by modeling the market dynamic as a repeated game between the nature (adversary) and the investor. We demonstrate that such framework yields analogous structure as the Black-
Lam, Henry, Liu, Zhenming
core  

Recent Advances in Sustainable Single‐Atom Catalysts from Biomass and Solid Waste: Design, Synthesis and Applications

Advanced Science, EarlyView.
Biomass‐ and solid waste‐derived sustainable single‐atom catalysts (Sus‐SACs) provide a cost‐effective and renewable approach to catalyst design. This review summarizes precursor selection, including AI‐assisted screening, synthesis strategies with emphasis on ultrafast methods, and advanced characterization techniques.
Hongzhe He, Yuhang Qiu, Ruoqun Zhang, Sasha Yang, Jingwei Wang, Jianglong Yu, Lian Zhang, Ning Chen, Baiqian Dai   +8 more
wiley   +1 more source

Competition law in the age of AI: Confronting algorithmic collusion in the smart economy

Smart Cities and Regional Development Journal
AI-driven pricing has become vital in the smart economy, boosted by advancements in IoT, AI, and big data. While robots and AI systems enhance efficiency and drive innovation across digital commerce platforms, they also raise competition law concerns ...
Chen LI, Ina VIRTOSU
doaj   +1 more source