Gradient descent

area: Machine learning · 7 papers in the last 7 days

\theta_{t+1} = \theta_t - \eta\, \nabla_\theta \mathcal{L}(\theta_t)

Moves parameters a step against the gradient of the loss; stochastic gradient descent uses mini-batches.

LaTeX: \theta_{t+1} = \theta_t - \eta\, \nabla_\theta \mathcal{L}(\theta_t)

Names searched for: gradient descent, SGD

Key findings

Gradient descent was mentioned in 38 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #29 of the 104 equations and models mentioned.
By journal category: AI (21), Operations Research (14), Economics (2) and Finance (1).
Most of them appeared in Journal of Optimization Theory and Applications (8), Machine Learning (5) and Computational Optimization and Applications (4).
Often mentioned together with Convolutional neural network (CNN) (13), Cross-entropy loss (10) and Logistic regression (logit) (9).
Datasets named in the same papers: OR-Library (12), ImageNet (6) and CIFAR-10 / CIFAR-100 (6).
From Apr 2024 to Sep 2026, 238 archived papers mentioned Gradient descent in their title, abstract or keywords, most of them in Jan 2025 (18).

Mentions over 30 months

Papers mentioning it by publication month, Apr 2024 to Sep 2026 (titles, abstracts and keywords)
Trend	Apr 24–Sep 24	Oct 24–Sep 25	Oct 25–Sep 26	30 months
	57	133	48	238

Papers mentioning Gradient descent, newest first.
Date	Title	Journal	Authors	Affiliations
2026-10-24	Optimal Portfolio Allocation with Gromov-Wasserstein Barycenter	Computational Economics	Alessandro Spelta, Nicoló Pecora, Mario Maggi	University of Pavia
2026-10-23	From pixels to profits: trading arbitrage portfolios based on image representations	Financial markets and portfolio management	Niklas Paluszkiewicz	Universität Ulm
2026-10-23	Hierarchical Interoceptive–Social Inference Dysregulation: A Computational Psychiatry Framework for Borderline Personality Disorder with Level-1 Active Inference Simulation and Implications for Cluster B Pathology	Cognitive Computation	Marco Fronzi	The University of Sydney
2026-10-22	An adaptive line-search-free multiobjective gradient method and its iteration-complexity analysis	Computational Optimization and Applications	Max L. N. Gonçalves, Geovani Nunes Grapiglia, Jefferson G. Melo	Universidade Federal de Goiás; UCLouvain
2026-10-21	Solving two-stage stochastic programming problems using alternating direction method of multipliers	Computational Optimization and Applications	Nouralden Mohammed, Montaz Ali	University of the Witwatersrand
2026-10-20	Test-Time Computing for Referring Multimodal Large Language Models	International Journal of Computer Vision	Mingrui Wu, Hao Chen, Jiayi Ji et al.	Xiamen University; Tsinghua University; Nankai University
2026-10-20	Convergence Analysis of Stochastic Accelerated Gradient Methods for Generalized Smooth Optimizations	Journal of Optimization Theory and Applications	Chenhao Yu, Yusu Hong, Junhong Lin	Zhejiang University
2026-10-19	Solutions of two-stage stochastic minimax problems	Mathematical Programming	Hailin Sun, Xiaojun Chen	Nanjing Normal University; Hong Kong Polytechnic University
2026-10-17	Beyond Likelihood Ratio Bias: Nested Multi-time Scale Stochastic Approximation for Likelihood-Free Parameter Estimation	Machine Learning	Zehao Li, Zhouchen Lin, Yijie Peng	Peking University; Nanjing University
2026-10-17	Decentralized Conjugate Gradient and Memoryless BFGS Methods	Journal of Optimization Theory and Applications	Liping Wang, Hao Wu, Hongchao Zhang	Nanjing University of Aeronautics and Astronautics; Louisiana State University
2026-10-15	A Cognitive, Quantum-Inspired Learning Framework for Energy-Efficient and Reliable Routing in Wireless Body Area Networks	Cognitive Computation	Soufiane Ben Othman, Naima Saeed	King Faisal University; University of Aden
2026-10-14	Dynamic gain neuromodulation attenuates stability gaps during continual joint training	Neural Networks	Alejandro Rodriguez-Garcia, Anindya Ghosh, Srikanth Ramaswamy	Newcastle University
2026-10-09	Lipschitz-free mirror descent methods for non-smooth optimization problems	Computational Optimization and Applications	Yuan Bowen, Mohammad Soud Alkousa	Beihang University; Innopolis University
2026-10-08	Adaptive parameter manifold learning for low-dimensional neural network optimization	Neural Networks	Zhekai Du, Wei Ao, Jieyan Liu et al.	University of Electronic Science and Technology of China
2026-10-07	Artificial intelligence technologies, skills demand and employment: Evidence from linked job ads	Labour Economics	Lennert Peede, Michael Stops	Institut für Arbeitsmarkt und Berufsforschung
2026-10-06	A variable smoothing for weakly convex composite minimization with manifold constraint via parametrization	Computational Optimization and Applications	Keita Kume, Isao Yamada	Tokyo Institute of Technology
2026-10-03	Uncertainty quantification for trustworthy deep learning: Methods and measures	Neural Networks	H. Martin Gillis, Thomas P. Trappenberg	Dalhousie University
2026-10-03	StoryReasoning dataset: Using chain-of-thought for scene understanding and grounded story generation	Pattern Recognition	Daniel A. P. Oliveira, David Martins de Matos	Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento; University of Lisbon; Instituto Superior Técnico
2026-10-01	First-Order Algorithms for Min–Max Problems with Non-linear Coupled Constraints	Journal of Optimization Theory and Applications	Ioannis Tsaknakis, Prashant Khanduri, Mingyi Hong et al.	University of Minnesota; Wayne State University
2026-10-01	Class-based many-objective neural architecture search for deep classifiers	Neural Computing and Applications	Guy Mardiks, Adham Salih, Amiram Moshaiov	Tel Aviv University; Braude College of Engineering Karmiel
2026-10-01	KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs	Machine Learning	Raffaele Scaringi, Alejandro Sierra Múnera, Gennaro Vessio et al.	University of Bari Aldo Moro; Hasso Plattner Institute; University of Potsdam; …
2026-10-01	Beyond Lipschitz: generalization and optimization analysis for adversarial training under Hölder-type conditions	Machine Learning	Hailiang Ye, Ziqi An, Feilong Cao	China Jiliang University; Zhejiang Normal University
2026-10-01	Fix Your Downsampling ASAP! Aliasing and Sinc Artifact Free Pooling in the Fourier Domain	International Journal of Computer Vision	Julia Grabinski, Steffen Jung, Janis Keuper et al.	Technische Hochschule Mannheim; University of Mannheim; Technische Universität Darmstadt; …
2026-10-01	Decentralized gossip learning and federated averaging for histopathology image classification	Neural Computing and Applications	Yusuf Öztürk, Bengisu Atli, Enes Goktekin et al.	Antalya Bilim Üniversitesi; Antalya Bilim University; Ankara University; …
2026-10-01	From 3D perception to safety reasoning: an intelligent hybrid framework for real-time underground mine monitoring	Expert Systems with Applications	Pasindu Ranasinghe, Simit Raval, Dibyayan Patra et al.	UNSW Sydney; University of Southern Queensland
2026-10-01	Inexact Proximal Point and Tseng Algorithms with Nonsummable Errors to Solve Monotone Inclusions	Journal of Optimization Theory and Applications	Ba Khiet Le, B.Sh. Mordukhovich, Michel A. Théra	Ton Duc Thang University; Wayne State University; Centre National de la Recherche Scientifique; …
2026-10-01	An Adaptive Framework for Robust Structural Shape Optimization Under Uncertainty	Journal of Optimization Theory and Applications	OĞUZ HAN ALTINTAŞ, Hamdullah Yücel	Middle East Technical University; Aselsan (Turkey)
2026-10-01	Parallelizable memory recurrent units	Neural Networks	Florent De Geeter, Gaspard Lambrechts, Damien Ernst et al.	University of Liège
2026-10-01	Monotone and Nonmonotone Linearized Block Coordinate Descent Methods for Nonsmooth Composite Optimization Problems	Journal of Optimization Theory and Applications	Yassine Nabou, Lahcen El Bourkhissi, Sebastian U. Stich et al.	University of Helsinki; Universitatea Națională de Știință și Tehnologie Politehnica București; Helmholtz Center for Information Security
2026-10-01	Coherent Local Explanations for Mathematical Optimization	Operations Research Letters	Daan Otto, Jannis Kurtz, Ş. İlker Birbil	Amsterdam University College; Amsterdam University of Applied Sciences; University of Amsterdam
2026-10-01	Effective algorithms for tensor-train decomposition via the UTV framework	Pattern Recognition	Yuchao Wang, Maolin Che, Yimin Wei	Chengdu University of Technology; Guizhou University; Fudan University
2026-10-01	Frictionless Hamiltonian Descent and Coordinate Hamiltonian Descent for Strongly Convex Quadratic Problems	Journal of Optimization Theory and Applications	Jun-Kun Wang	University of California San Diego
2026-10-01	Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses	International Journal of Computer Vision	Hao Fang, Yixiang Qiu, Hongyao Yu et al.	Tsinghua Shenzhen International Graduate School; Tsinghua University; Harbin Institute of Technology; …
2026-09-30	Towards optimized forward–forward training for neural networks	Artificial Intelligence Review	Yomna Abdulgawad Elnady, Amany Mahmoud Sarhan, Mohammad Ali Eita	Tanta University; ElSewedy University of Technology
2026-09-29	MAdam: MLMC Adam under Markovian Noise with Application to Average-Reward Policy Optimization	Journal of Optimization Theory and Applications	Andrey Veprikov, Vladimir Solodkin, Alexander Chernyavskiy et al.	Innopolis University
2026-09-28	Differentially Private Stochastic Gradient Descent for Outcome Weighted Learning	Machine Learning	Aoli Yang, Jun Fan, Yunwen Lei et al.	Zhejiang Normal University; Hong Kong Baptist University; University of Hong Kong
2026-09-28	CausalCACTUS: A Causally Consistent and Context-Aware Framework for Counterfactual Explanations	Machine Learning	Zhendong Wang, Diego García, José María Enguita et al.	KTH Royal Institute of Technology; Universidad de Oviedo
2026-09-28	DAMEL: Dual-axis multi-expert learning for class-imbalanced learning	Knowledge-Based Systems	Hyuck Lee, Taemin Park, Heeyoung Kim	Korea Advanced Institute of Science and Technology

Cite this page

Scholar4AI. (2026). Gradient descent. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/equations/gradient-descent

@misc{scholar4ai-equations-gradient-descent,
  author = {{Scholar4AI}},
  title = {Gradient descent},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/equations/gradient-descent}},
  urldate = {2026-10-26},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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