SINDI: an Efficient Index for Approximate Maximum Inner Product Search on Sparse Vectors
Ruoxuan Li, Xiaoyao Zhong, Jiabao Jin, Peng Cheng, Wangze Ni, Lei Chen, Zhitao Shen, Wei Jia, Xiangyu Wang, Xuemin Lin, Heng Tao Shen, Jingkuan Song
https://arxiv.org/abs/2509.08395
Inner-product Functional Encryption with Fine-grained Revocation for Flexible EHR Sharing
Yue Han, Jinguang Han, Liqun Chen, Chao Sun
https://arxiv.org/abs/2509.07804 https://…
Energy Estimates for Fractional Evolution Equations
Paulo M. Carvalho-Neto, Cicero L. Frota, Juan C. Oyola Ballesteros, Pedro G. P. Torelli
https://arxiv.org/abs/2508.05780 http…
Symmetrized operators or modified integration measure in Generalized Uncertainty Principle Models
Michael Bishop, Daniel Hooker, Doug Singleton
https://arxiv.org/abs/2509.20466 …
Transients in black hole perturbation theory
J\'er\'emy Besson, Javier Carballo, Christiana Pantelidou, Benjamin Withers
https://arxiv.org/abs/2507.16493
A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
Johnny R. Zhang (Independent Researcher), Xiaomei Mi (University of Manchester), Gaoyuan Du (Amazon), Qianyi Sun (Microsoft), Shiqi Wang (Meta), Jiaxuan Li (Amazon), Wenhua Zhou (Independent Researcher)
https://arx…

A Universal Banach--Bregman Framework for Stochastic Iterations: Unifying Stochastic Mirror Descent, Learning and LLM Training
Stochastic optimization powers the scalability of modern artificial intelligence, spanning machine learning, deep learning, reinforcement learning, and large language model training. Yet, existing theory remains largely confined to Hilbert spaces, relying on inner-product frameworks and orthogonality. This paradigm fails to capture non-Euclidean settings, such as mirror descent on simplices, Bregman proximal methods for sparse learning, natural gradient descent in information geometry, or Kullb…
A novel generalized inner product-based wave scattering from an underwater source in a compressible ocean
R. Pethiyagoda S. Das, B. Wilks, M. H. Meylan
https://arxiv.org/abs/2509.19196
Higher Structures on Boundary Conformal Manifolds: Higher Berry Phase and Boundary Conformal Field Theory
Yichul Choi, Hyunsoo Ha, Dongyeob Kim, Yuya Kusuki, Shuhei Ohyama, Shinsei Ryu
https://arxiv.org/abs/2507.12525
Smoothness in the space of bounded linear operators on semi-Hilbert space
Somdatta Barik, Souvik Ghosh, Kallol Paul, Debmalya Sain
https://arxiv.org/abs/2509.00335 https://
MaxWave: Rapid Maximum Likelihood Wavelet Reconstruction of Non-Gaussian features in Gravitational Wave Data
Sudhi Mathur, Neil J. Cornish
https://arxiv.org/abs/2508.13377 https…
Multi-Partitioned Meshfree Quantum Finite Particle Method: A Hybrid Quantum Framework for Fluid Flow
Yudong Li, Wenkui Shi, Yan Li, Chunfa Wang, Ling Tao, Zhuojia Fu, Moubin Liu, Zhiqiang Feng
https://arxiv.org/abs/2509.11276