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ORCIDIEEE Signal Processing Magazine, Volume 43
Volume 43, Number 1, January 2026
- Kostas N. Plataniotis
:
IEEE Signal Processing Society: State of Society [State of Society]. 3-4 - Davide Dardari, Giulia Torcolacci, Gianni Pasolini, Nicolò Decarli, Michail Matthaiou:
Over-the-Air Electromagnetic Signal Processing: From fundamentals to emerging paradigms. 6-28 - Danilo P. Mandic, Mónica F. Bugallo, Chrisina Jayne, Irwin King:
Artificial Intelligence for Education: A Signal Processing Perspective: Part II: From Human-AI Cocreativity to Educational Equity [From the Guest Editors]. 29-31 - Jarvis Haupt, Qin Lu, Yanning Shen, Jia Chen, Yue Dong, Dan McCreary, Mehmet Akçakaya, Georgios B. Giannakis:
Deploying AI for Signal Processing Education: Selected challenges and intriguing opportunities [Special Issue on Artificial Intelligence for Education: A Signal Processing Perspective]. 32-46 - Kurt Butler, Mónica F. Bugallo, Petar M. Djuric:
Artificial Intelligence Foundations: Building essential machine learning skills and understanding [Special Issue on Artificial Intelligence for Education: A Signal Processing Perspective]. 47-55 - Maoquan Zhang, Bisser Raytchev, Xiujuan Sun:
REALM: A relevance-driven layered protocol for human-AI collaboration in STEM education [Special Issue on Artificial Intelligence for Education: A Signal Processing Perspective]. 56-68 - Yuchen Wang, Pei-Duo Yu, Chee Wei Tan:
Future-Proofing Programmers: Optimal knowledge tracing for artificial intelligence-assisted personalized education [Special Issue on Artificial Intelligence for Education: A Signal Processing Perspective]. 69-82 - Alexander Jenkins, Emma Rainbow, Imad Jaimoukha, Fu Siong Ng, Ljubisa Stankovic, Milos Dakovic, Danimir Mandic, Danilo P. Mandic:
Fair and Skill-Diverse Student Group Formation: A graph-theoretic approach [Special Issue on Artificial Intelligence for Education: A Signal Processing Perspective]. 83-97 - Liming Xiu, Ulisses Braga-Neto:
Transcending Reductionism and Dualism: Philosophical Critique of Electronics and a Vision for Brain-Mimicking Artificial Intelligence Under Moore's Law 2.0 [Perspectives]. 98-107 - Pushpendra Singh, Prisha Singh, Anubha Gupta, Rodrigo Capobianco Guido:
A Pedagogical Reconceptualization of Complex Numbers as Two-Dimensional Real Numbers: A Signal Processing Perspective [Lecture Notes]. 109-122
Volume 43, Number 2, March 2026
- Tülay Adali:
The Nasreddin Hodja Principle and the Mathematics of Deep Learning [From the Editor]. 3-4 - Laura Balzano, Joan Bruna Estrach, Gitta Kutyniok, Robert Nowak, Jong Chul Ye:
Guest Editorial for Part 1 of the Special Issue on the Mathematics of Deep Learning [From the Guest Editors]. 6-8 - Rémi Gribonval, Elisa Riccietti, Quoc-Tung Le, Léon Zheng:
Rapture of the Deep: Highs and lows of sparsity in a world of depths. 10-23 - Liangzu Peng, René Vidal:
Continual Learning Through the Lens of Adaptive Filtering: A mathematical tutorial. 24-36 - Yao Xie, Xiuyuan Cheng:
Flow-Based Generative Models as Iterative Algorithms in Probability Space: An intuitive mathematical framework [Special Issue on the Mathematics of Deep Learning]. 37-50 - Martina Pastorino, Gabriele Moser, Sebastiano B. Serpico, Josiane Zerubia:
Probabilistic Graphical Models Meet Deep Learning for Semantic Segmentation: Mathematical connections and recent developments. 51-63 - Adalbert Fono, Manjot Singh, Ernesto Araya, Philipp Christian Petersen, Holger Boche, Gitta Kutyniok:
Mathematical Foundations of Spiking Neural Networks: Strengths, challenges, and computational paradigm potential [Special Issue on the Mathematics of deep Learning]. 64-76 - Ismail Alkhouri, Evan Bell, Avrajit Ghosh, Shijun Liang, Rongrong Wang, Saiprasad Ravishankar:
Understanding Untrained Deep Models for Inverse Problems [From the Guest Editors]: Algorithms and theory. 77-92 - Zhenyu Liao, Michael W. Mahoney:
Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models [Special Issue on the Mathematics of Deep Learning]. 93-106 - Ricardo Augusto Borsoi, Konstantin Usevich, Marianne Clausel:
Low-Rank Tensor Decompositions for the Theory of Neural Networks: Understanding deep learning through the lens of tensor formats [Special Issue on the Mathematics of Deep Learning]. 107-121 - Ulisses Braga-Neto, Yidong Chen:
In Memoriam: Edward R. Dougherty [In Memoriam]. 122
Volume 43, Number 3, May 2026
- Kostas N. Plataniotis:
From Coordination to Execution: Positioning the IEEE Signal Processing Society at the Core of IEEE's Artificial Intelligence Ecosystem [From the Editor]. 3-4 - Laura Balzano, Joan Bruna Estrach, Gitta Kutyniok, Robert Nowak, Jong Chul Ye:
Guest Editorial for Part 2 of the Special Issue on the Mathematics of Deep Learning [From the Guest Editors]. 5-7 - Randall Balestriero, Yann LeCun:
Spectral Graph Theory: The mathematics of self-supervised learning [Special Issue on the Mathematics of Deep Learning]. 8-20 - Thomas Pethick, Kimon Antonakopoulos, Antonio Silveti-Falls, Leena Chennuru Vankadara, Volkan Cevher:
Training Neural Networks at Any Scale: An exposition. 21-36 - Hancheng Min, Lachlan Ewen MacDonald, René Vidal:
On the Convergence, Implicit Bias, and Edge of Stability of Gradient Descent in Deep Learning: Reviewing recent progress [Special Issue on the Mathematics of Deep Learning]. 37-51 - Laura Balzano, Tianjiao Ding, Benjamin D. Haeffele, Soo Min Kwon, Qing Qu, Peng Wang, Zhangyang Wang, Can Yaras:
An Overview of Low-Rank Structures in the Training and Adaptation of Large Models: From Implicit Low-Dimensionality to Efficient Training and Fine-Tuning [Special Issue on the Mathematics of Deep Learning]. 52-70 - Siliang Zeng, Luca Viano, Chenliang Li, Jiaxiang Li, Markus Wulfmeier, Stefano Ermon, Alfredo García, Mingyi Hong:
Aligning Large Language Models With Human Feedback: Mathematical foundations and algorithm design [Special Issue on the Mathematics of Deep Learning]. 71-85 - Emi Zeger, Mert Pilanci:
Unveiling Hidden Convexity in Deep Learning: A sparse signal processing perspective [Special Issue on the Mathematics of Deep Learning]. 86-101 - Lai Tian, Anthony Man-Cho So:
Computational Nonsmooth Analysis: Modern applications and recent developments [Special Issue on the Mathematics of Deep Learning]. 102-114 - Felix Sarnthein, Arshia Afzal, Razvan Pascanu, Antonio Orvieto, Caglar Gulcehre, Jonas Geiping, Francesco Tonin, Albert Gu, Volkan Cevher:
Sequence Modeling Architectures: Foundations [Special Issue on the Mathematics of Deep Learning]. 115-129
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